LEAD DATA ARCHITECT SKILLS, EXPERIENCES, AND JOB REQUIREMENTS
Published: Jan 08, 2026 - The Lead Data Architect leads enterprise data architecture programs and delivers scalable event-based and big data designs that align models, assets, and integration patterns with business goals. This role requires expertise in streaming and data engineering using Kafka, Spark, Databricks, cloud warehouses, and data catalogs with profiling standards. The lead also evaluates technologies through structured RFP scoring, defines API architecture approaches, and enables AI/ML foundations through automation-ready architecture.
Essential Hard and Soft Skills for a Lead Data Architect Resume
- Data Architecture
- Data Modeling
- Solution Architecture
- ETL Development
- Data Integration
- Data Governance
- Metadata Management
- Data Quality
- Performance Tuning
- Data Strategy
- Team Leadership
- Stakeholder Management
- Stakeholder Collaboration
- Requirements Analysis
- Effective Communication
- Problem Solving
- Workshop Facilitation
- Project Leadership
- Team Coaching
- Roadmap Planning
Summary of Lead Data Architect Knowledge and Qualifications on Resume
1. BS in Data Science with 7 years of Experience
- Experience designing and implementing Enterprise Data and Analytics Architectures
- Strong background in leading, facilitating activities in the area of expertise (internal teams and multivendor environment, remote included)
- Good interpersonal and communication skills
- Fluent in English, both oral and in written text
- Experience in working with compliance (data privacy and quality, access, and authorization concepts) and cybersecurity requirements
- Experience in DevOps methodology and principles such as cloud-based services (Azure), Infrastructure as a code (Terraform)
- Experience in data science/cloud-based machine learning platforms, Azure Data Platform, SQL Data Warehouse, Data Lake and Databricks, Azure Data Factory, Azure Synapse Analytics, SAP solutions for data services (BI/ BO/ BW)
- Working experience in driving big data initiatives and navigating complex data challenges
- Possess a strong understanding of the big data landscape
- Previous experience working in and with data lakes, data warehouses, streaming platforms, and cloud platforms
- Working experience in data mining, machine learning, and data science
- Knowledge of integration packages/enterprise messaging (middleware packages)
2. BS in Cloud Computing with 6 years of Experience
- Experience writing production-grade code using such as Python, Java, Spark, Scala, and other languages in support of ETL, ML, and Analytics
- Wide-ranging analytics experience, in areas such as SQL-based analytics, business intelligence, and reporting (machine learning/ statistical modeling)
- Experience or interest in identifying, developing, and implementing Analytics and AI/ML techniques to improve engagement productivity, increase efficiencies, mitigate risks, resolve issues, and optimize cost savings and efficiencies for each client
- Experience working with Data Science and related technologies
- Experience with system automation and automated provisioning using such technologies as CloudFormation, Terraform, Ansible, Chef, or Puppet
- Familiarity with Microservices, Event-Driven Architecture, and CQRS
- Strong knowledge about Agile techniques such as User Stories, Continuous Integration, Test Driven Development, Continuous Testing, Pairing, Automated Testing, Burn Down Metrics, Velocity, etc.
- Strong knowledge of software development processes and procedures to understand team needs, including fundamentals of iterative and incremental development
- Working experience in the Supply chain industry
- Exposure to Computer Vision, Natural Language Processing, general Machine Learning, and Deep Learning technologies
3. BS in Computer Science with 9 years of Experience
- Enterprise data architecture experience
- Experience with architectural patterns, involved in building APIs, microservices, event streams, and high-throughput systems
- Knowledge and experience with an enterprise service bus
- Develop and document integration controls to satisfy audit requirements
- Experience working within the AWS ecosystem
- Possess Master Data Management skills (MDM)
- Data engineering experience, with knowledge of the Agile development process
- Experience in architecting and developing large-scale MDM, data warehousing, data lake and data integration projects
- Experience with data governance tools, e.g., Collibra
- Experience in performance monitoring and performance tuning
- Must have AWS certifications
- Working experience in software development, solutions architecture, or architect roles
- Experience in designing, developing, and architecting enterprise data systems
- Working experience with distributed data management, data storage including databases (relational, NoSQL), data analysis, data processing, data transformation, high availability, and scalability
- Solid understanding and experience in the reporting domain - operational and analytics
4. BS in Software Engineering with 5 years of Experience
- Must have strong leadership skills
- Excellent communication and presentation skills
- Domain knowledge in one or more corporate functions such as HR, Finance
- Excellent problem-solving skills with innovative thinking and a proactive approach
- Ability to recommend and implement best practices and processes
- Experience in Agile development methodologies
- Experience implementing Delta Lake and Data Lakehouse
- Must have Microsoft Azure Certifications related to Data and Analytics (e.g., Azure Data Engineer DP200/201, and/or 70-467, or related MCSE)
- Strong knowledge of databases such as Oracle and SQL
5. BS in Computer Engineering with 6 years of Experience
- Detailed understanding of data constructs, i.e., data modelling, data design, data integration, data reporting and visualisation
- Understanding of data lake architectures and best practices for storing, loading and retrieving, including data migration strategies
- Cloud awareness and experience of the leading cloud providers and services, e.g., AWS, GCP, Azure
- Ability to convey and articulate complex, abstract technical concepts to technical and non-technical audiences
- Experience with and comfortable working with C-suite leadership
- Extensive commercial experience working with complex and large datasets in cloud environments (AWS, Azure, Google Cloud)
- Extensive experience with CI/CD and data orchestration tools (e.g., Airflow, Prefect)
- Very strong SQL usage and query optimization skills
- Strong software engineering skills (Python)
- Deep understanding of big data tools and environments
6. BS in Cybersecurity with 8 years of Experience
- Experience working with the physical and logical architecture of data systems
- Expert-level experience defining data architecture (conceptual, logical and physical)
- Knowledge of at least one data modeling software tool such as Erwin, ER/Studio, or Power Designer
- Experience with ETL and business intelligence tools
- Must have or be eligible for a security clearance due to contractual requirements
- Proven experience in architecting modern, scalable data platforms using Snowflake and dbt at the core
- Experience with modern data ingestion tools such as FiveTran and Azure Data Factory
- Experience with modern orchestration tools such as AirFlow
- Experience implementing and enforcing CICD best practices with Git
- Knowledge of data modeling best practices
- Highly proficient in SQL and Python
- Experience operating in an agile development environment
- Exposure to data science practices
7. BS in Business Analytics with 7 years of Experience
- Experience implementing analytics data solutions by working with and leveraging Microsoft Azure resources such as Azure Data Lake Storage, Azure Data Factory, Synapse, Data Bricks, Logic Apps, Power BI and Client Studio
- Experience in data warehousing with expert knowledge of dimensional modeling concepts and performance tuning
- Ability to evaluate existing data models and physical databases for variances, discrepancies, and redundancies
- Ability to independently perform data profiling and analysis to understand source data
- Understanding of the role of data security and privacy compliance and related best practices in their implementation
- Experience using Erwin Data Modeler R9.7 or later
- Experience with data lineage and data cataloging tools such as Informatica EDC and Alation Data Catalog
- Experience with data virtualization platforms such as Dremio or Denodo
- Working knowledge and experience with Python, Scala, or R
- Experience in Computer Science, Information Systems, or related disciplines
8. BS in Applied Mathematics with 6 years of Experience
- Experience in Enterprise Data Architecture or similar roles with an in-depth understanding of data management, database structure principles, application design, cloud technologies and systems analysis
- Architecture and Engineering data leader proficient in modern cloud computing, advanced analytics, architectures, and patterns
- Experienced in introducing and integrating new technologies at scale
- Knowledge of systems development, including system development life cycle, project management approaches and requirements, design and testing techniques
- Proficiency in data modeling and design, including SQL development and database administration
- Knowledge about MDM tools and Data Governance tools
- Knowledge of Collibra, Data Anonymization tools like PKProtect
- Working understanding of the usage of data for data science and machine learning
- Experience with Master Data Management
- Experience in Physical and Logical Data Modeling
- Experience with DataOps and DevOps
9. BS in Network Engineering with 5 years of Experience
- Strong math and analytical skills
- In-depth knowledge of SQL, NOSQL and other types of datastores
- Strong expertise in big data and distributed cluster computing technologies
- Must have Cloud computing (Azure, AWS) such as Datastores, SQL Engines, Blob Storage, Scheduling, and Machine Learning stack
- Experience working with multiple file structures (Mainframe, Flat files, JSON, XMLs)
- Experience in Unix/Linux operating systems, with scripting expertise
- Programming skillsets in at least one of these languages such as Java, Scala, Python
- Able to compile and organize statistical information retrieved and present findings to management
- Experience working with private and sensitive personal information
- Confident in decision-making and the ability to explain processes or choices
- Financial regulatory reporting (CCAR, CECL, Liquidity, etc.)
- Knowledge of Banking products lifecycle such as Checking, Mortgages, Loans, Treasury, Cash Management, etc.
10. BA in Operations Management with 9 years of Experience
- Experience in technical leadership, managing data architecture teams, and setting architectural direction
- Proven experience in business requirements elicitation and definition, and translating business requirements into high-level design models
- Hands-on knowledge of foundational data architecture such as data warehouses and lakes, dimensional modeling and data life cycle management
- Strong attention to detail, ability to think critically and analytically
- Excellent SQL skills
- Work experience with enterprise data warehousing, data management, business intelligence and large-scale data solutions
- Knowledge in the areas of Reference Data, Data Quality, and Metadata Management
- Understanding of Taxonomies and Ontologies
- Familiarity with Big Data technologies including Hadoop, Hive, Spark, NoSQL
- Experience with OLAP, columnar databases, and MPP databases
- Experience with languages for data manipulation and analysis, like Python or R
- Good knowledge of data privacy practices and laws (internationally)
- Experience in inventing data solutions
- Strong sense of ownership, passion to build quality products for massive scale in a collaborative and agile environment, and an excitement to learn
- Familiarity with the video game data domain and its life cycle
11. BS in Data Science with 7 years of Experience
- Proven experience in driving architectural change that transforms and optimises complex businesses
- Experience within a large, complex enterprise
- Experience working on evolving enterprise Data Architecture projects
- Management and team mentorship experience
- Mastery of Azure, Databricks and Data Factory
- Proven experience with financial services or closely related industries (e.g., insurance/consulting)
- Must be a strong team player who demonstrates flexibility and pro-activeness to deliver business outcomes
- Extensive work experience as a full-stack software engineer, architecting and building structured, scalable web-based solutions and UIs using modern platforms and frameworks
- Strong problem-solving skills, understanding of data structures and algorithms
- Must have Data engineering, data modelling, and data pipeline knowledge
- Experience with API management, test-driven development, relational and NoSQL Database Systems (such as Snowflake)
- Familiarity with Spark or Databricks
12. BS in Software Engineering with 3 years of Experience
- Strong experience in data warehouse implementation
- Strong T-SQL
- Must have DBA experience for basic management of Microsoft Server
- Strong leadership skills and experience
- Demonstrable knowledge and experience of PaaS and IaaS
- Experienced in using Informatica and AWS
- Previous experience with Salesforce CRM and Salesforce Marketing Cloud
- Familiar with Pseudonymisation concepts
13. BS in Computer Engineering with 4 years of Experience
- Strong analytical and problem-solving skills
- Strong interpersonal skills
- Skill to partner with cross-functional teams using strong written and verbal communication skills
- Self-starter who completes tasks without excessive supervision
- Passionate about applying data strategy to achieve business outcomes
- Experience in data architecture and design, for both structured and unstructured data, data modeling, architecting and delivering highly scalable and flexible, cost-effective, cloud-based enterprise data solutions.
- Deep database knowledge and proficient with SQL
- Experience developing software code in one or more programming languages (i.e., Python)
- Understanding of Apache Spark/Hadoop, relational and NoSQL databases
14. BS in Statistics with 5 years of Experience
- Experience as a Data Architect, or similar role
- Experience within Data/ Data pipelines /Big Data/Advanced Analytics
- Expertise in the design and implementation of enterprise data stores, data warehouses, data governance, data quality management, and metadata management
- Experience building data pipelines with Azure
- Hands-on experience in the migration of on-prem (traditional data warehouse and big data) data solutions to the Azure cloud
- Extensive experience with Azure Databricks, ADF, HDInsights, Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure Stream Analytics
- Experience with migrating SAP BO or IBM Cognos to Azure
- Ability to mentor the team on cloud technologies
- Experience in big data distributed storage processing and streaming architectures such as Hive, data lake, Spark/Python, Azure Analytics, etc.
15. BS in Business Analytics with 7 years of Experience
- Experience with Data Lake Infrastructure, Data Warehousing, Data Modelling and Data Analytics tools by working with agile methodology
- Experience developing enterprise data models
- Cloud data engineering experience in at least one cloud (Azure, AWS, GCP)
- Experience in at least one data modeling tool (ER/Studio, Erwin)
- Experience with the integration of multi-cloud services with on-premises technologies
- Experience with at least one MPP database technology such as Redshift, Synapse or Snowflake
- Excellent communication skills, both verbal and written, along with a strong ability to influence senior-level management and stakeholders
- Proven track record of leading, mentoring, hiring and scaling data teams
- Comfortable with change, especially that which arises through company growth
- Ability to understand and translate business requirements into data and technical requirements
- High degree of organization and ability to manage multiple, competing projects and priorities simultaneously
16. BS in Cloud Computing with 6 years of Experience
- Demonstrated hands-on experience in designing, building and implementing Microsoft solutions based on Azure IaaS and PaaS
- Solid experience with the Azure Data platform including Azure Synapse, Data Factory, Data Bricks, Data Lake, and Power BI
- Deep experience in the SQL Server product suite, including SSAS, SSIS and SSRS
- Experience designing and implementing solutions using the Microsoft Power BI platform, or extensive tabular modelling experience including DAX
- Exposure to AI, IoT, and Machine Learning
- Highly developed conceptual and analytical skills combined with sound judgement
- Proven ability to develop technical requirements based on business imperatives
- Ability to write quality, high-level level and detailed architectural diagrams, strategic roadmaps and technical documentation that communicate customer vision
- Must have MS Certifications/exposure to industry and IT methodologies and frameworks such as TOGAF, ITIL and Agile
17. BS in Database Management with 9 years of Experience
- Hands-on experience working in enterprise-scale data warehousing, data architecture, and/or data engineering environments
- Previous work as an Enterprise Architect with a good understanding of Enterprise Architecture as a practice
- Working experience in designing, implementing, and building pipelines (ETL) that deliver data with measurable quality under the SLA
- Hands-on data modeling experience, especially dimensional data modeling
- Must know Tableau, Power BI, MicroStrategy or other Data visualization tools
- Deep experience and strong grasp of the ServiceNow platform and underlying data model and related concepts, including ServiceNow’s Common Service Data Model (CSDM) and Configuration Management Database (CMDB)
- Ability to judiciously weigh the cost/benefit of all meta model, data model, and data schema customizations
- Strong understanding of core infrastructure components (servers, network, storage)
- Experience with Enterprise Data Governance, Big Data Solutions, Master Data Management, Data Privacy and Security, Machine Learning, and Data Pipeline Operations
- Experience with building analytic solutions applicable to Sales, Finance, Product, and Marketing organizations in an enterprise
- Experience implementing operational best practices such as monitoring, alerting, and metadata management
- Experience managing, measuring, and improving data quality in a data warehouse
- Communication skills including the ability to identify and communicate data-driven insights
- Great analytical and problem-solving skills
18. BA in Information Management with 7 years of Experience
- Previous work in data architecture
- Ability to incorporate Enterprise data strategies in delivered Solutions
- Ability to build and manage enterprise data and object models, leveraging both industry and application-specific service models
- Experience with large, broadly scoped Data Architecture programs
- Experience with data catalogs, profiling tools and processes
- Experience with modern event-based data architecture, Kafka, streaming analytics, etc.
- Familiar with training and deployment of AI Machine Learning models and automation
- Experience with API architectures such as web services, ESB, and managed API
- Ability to evaluate and assess existing legacy data assets
- Able to create as-is and to-be architecture artifacts
- Well-versed in the Data domains (Data Warehousing, Analytics, BI, Big Data, Operational Data Store, Metadata, Master Data, Unstructured Data, ETL, ESB)
- Experience in architecture governance, controls, and peer reviews of data, security, and cloud
- Experience in information technology
19. BS in Computer Science with 6 years of Experience
- Able to support the project team with the required expertise
- Strong hands-on experience working as a Cloud Data Solutions Architect
- Expert in Data Lake, Data Warehouse Architecture and Data Modelling
- Experienced in leading a team of Data Architects and data engineers
- Working experience in Data Management, Data Warehousing, Database Administration and Data Access solutions
- Proven experience in model-based database development and data access approach
- Proven experience in configuring and maintaining databases and data access tools
- Working experience in back-end development and/or database management, and/or designing, creating, developing, and managing data
- Ability to articulate clarity to design and architectural needs to business, developers, product owners, and product managers
- Ability to provide tools and direct developers in building tools to access the data layer
- Ability to automate and facilitate the continuity of environments for dev, test, demo, beta, and production
20. BS in Information Technology with 8 years of Experience
- Experience in data architecture, data modelling, or data warehouse design
- Good communication and data presentation skills with the ability to pitch and explain to business and technical stakeholders at various levels of the organisation
- Deep experience of relational and dimensional modelling techniques
- Experience working with data modelling tools such as Erwin, Idera ER Studio or SAP PowerDesigner and integrating them into the development process
- Experience in building and enforcing standards for data architecture across multiple delivery teams
- Strong proficiency in SQL
- Experience working with both structured relational and semi-structured data sets
- Experience of working with cloud-native data warehouse technologies such as Snowflake, AWS Redshift, or Azure Data Warehouse as well as relational databases such as MySQL or Postgres
- Experience working with a Master Data Management (MDM) system
- Experience modeling with Business Intelligence platforms such as Tableau or Looker
- Experience in designing for a warehouse based on the Data Vault 2.0 methodology
- Direct experience of implementing SAP PowerDesigner
- Experience of working across a global organisation
21. BS in Software Engineering with 5 years of Experience
- Significant experience with Python and all associated libraries
- Significant experience in SQL (queries, stored procedures)
- Strong knowledge/experience with SQL ORMs such as PyMySQL and SQLAlchemy
- Experience using Flask/Django, NumPy, Pandas, Jupyter Notebooks
- Experience with JavaScript frameworks (Angular, Vue, React)
- Hands-on experience in working with AWS services like Elastic Beanstalk, Lambda, SNS, SQS, API Gateway, S3 Secrets Manager, RDS, Athena, and Glue
- Experience in building data science models and/or financial/economic research
- Prowess with large dataset management, cleaning, and manipulation
- Ability to multitask effectively while maintaining accuracy
22. BS in Computer Engineering with 4 years of Experience
- Experience with data analytics, BI, data reporting and visualization, all aspects of data management such as data governance, data mastering, data warehousing, database management, and metadata management
- Experience designing and implementing data ingestion techniques for real-time and batch data pipelines from disparate data sources
- Experience with ETL tools
- Experience with the agile development methodology
- Ability to think strategically about business and technical challenges in an enterprise environment
- Familiar with developing and implementing data models for analytic use
- Keen eye for systems thinking and process design, especially with respect to scalability and automation
- Experience with AWS big data technology stack and cloud-based architecture
23. BS in Information Systems with 6 years of Experience
- Experience installing and managing Microsoft Windows servers, Linux servers, Active Directory, and Data Center infrastructure solutions
- Ability to manage and monitor vendor hardware and software network acquisitions
- Ability to work independently to resolve highly technical system issues
- Thorough knowledge of the principles of preventative maintenance techniques on the storage and server environment to ensure systems remain
- Comprehensive knowledge of the acquisition and installation of network security software and conduct intrusion testing
- Comprehensive knowledge of the major components of storage and server infrastructure - hardware, software, cabling systems
- Ability to utilize and manage software systems of the Microsoft Office suite, Microsoft Server/Active Directory, and firewalls
- Ability to evaluate and manage software and database systems of CommVault, VMware ESXi, Microsoft and Linux
- Ability to communicate with users to define system requirements and resolve problems
- Effective collaboration with peers and vendors on the efficiency of the systems supported
24. BS in Cybersecurity with 8 years of Experience
- Data management and/or applications experience, with a proven track record of success in a similar role
- SAP implementation experience with SAP ECC 6.0 or SAP S/4 (global implementation experience)
- Working experience in SAP MDG
- Experience with at least one industry-leading ETL tool (e.g., Informatica)
- Experience with data quality or other tools
- Experience leading and executing mock data loads and testing cycles supporting ERP implementations
- Experience in a product manufacturing and/or project environment
- Experience managing technology projects
- Strong business acumen
- Superior conceptual, analytical, change management and organizational skills
- Working experience in Agile and DevOps
- ITIL Foundations or a more advanced level of ITIL certification
- Strong organizational, multi-tasking and interpersonal skills
- Strong verbal, written, and presentation skills
- Ability to analyze and interpret critical path, draw conclusions, and prepare clear and concise analyses and recommendations
25. BS in Business Analytics with 7 years of Experience
- Expertise and experience in developing data science solutions using tools such as Python, R, TensorFlow, in products such as Zeppelin / Jupyter Notebooks
- Expertise and experience in developing solutions across multiple cloud applications including Azure, AWS, Google, Oracle and IBM Cloud providers
- Knowledge of hybrid cloud data development and containerization techniques including Kubernetes, Docker, Cloud Foundry and IBM Cloud Pak for Data
- Able to provide thought leadership, advice and guidance to senior client business and IT stakeholders on matters of big data, analytics, data management, governance and organizational design
- Able to deliver large-scale enterprise big data solutions using a delivery team distributed across multiple time zones and geographies
- Able to translate requirements/problem statements and scope and estimate them into solution proposals/projects
- Able to articulate the success criteria of solutions, capabilities or applications
- Able to tackle and articulate problems from different perspectives
- Able to implement data governance, master data management and/or data quality initiatives at an enterprise level
- Able to lead and manage an enterprise data organization including both permanent and contracting resources
26. BS in Management Information Systems with 5 years of Experience
- Strong attention to detail and commitment to data integrity
- High level of organization, creativity and resourcefulness
- Excellent written and verbal communication skills
- Ability to work in an agile team environment, complete assignments promptly and flexibility
- Experience with Business Intelligence Tools like Power BI and Tableau
- Experience with Elasticsearch, GraphQL
- Basic DevOps experience – working with CI/CD, containers, etc
- Experience with Machine Learning (ML) on large datasets
- Experience with NoSQL databases
- Familiarity with Azure or GCP
27. BS in Database Management with 9 years of Experience
- Experience with tools such as Azure DevOps, Python, SharePoint, Office 365, Microsoft Teams, etc.
- Experience in configuring and implementing Azure Storage, Azure Data Factory, Azure Data Lake, Azure SQL Server Data Warehouse and Azure SQL Server database
- Good understanding of AZURE components, storage and compute services
- Experienced in Data modelling and data architecture design
- Knowledge in ETL, data integration and data migration design
- Experience in configuring private and public-facing Azure load balancers, etc.
- Experience with Data testing, including the ability to create test plans, test cases, execute test cycles, etc.
- Experience is creating the effort estimation, timelines for all new projects/programs
- Expertise in Dimensional modeling and exposure to Vault data modeling techniques in an agile environment
- Expertise in SQL Server database architecture, T-SQL development, and tuning
- Solid experience in Microsoft traditional data warehousing (SQL Server, SSIS, etc.)
- Experience in industry Canonical modeling, Master data management, and metadata-driven solutions
- Familiarity with predictive analysis and data visualization techniques using relevant tools (e.g., PowerBI, Tableau, D3.js, R, etc.)
28. BS in Network Engineering with 4 years of Experience
- Experience of IT platform implementation in a highly technical and analytical role
- Experience with Data Analytics platform implementation
- Hands-on experience in the implementation and performance tuning of Hadoop/Spark implementations
- Ability to think strategically about business, product, and technical challenges in an enterprise environment
- Understanding of Apache Spark/Hadoop and the Data Analytics ecosystem
- Experience with one or more relevant tools (Atlas, Sqoop, HBase, Flume, Kinesis, Kafka, Oozie, Hue, Zookeeper, Ranger, Delta Lake, Avro, etc.)
- Familiarity with one or more SQL-on-Hadoop technologies (Hive, Pig, Impala, Spark SQL, Presto)
- Experience developing software code in one or more programming languages (Java, JavaScript, Python, etc.)
29. BA in Information Management with 7 years of Experience
- Work experience in reporting, BI, and data warehousing for corporate functions
- Experience leading information architecture as part of large, cross-functional teams supporting development of major enterprise cloud or SaaS products, features and services
- Experience executing large-scale programs to implement and maintain architectures involving OLTP, OLAP and Data Warehousing
- Experience in leading data strategy engagements involving the architecture of modern data platforms
- Understanding of the information security standards and how to design the information architecture per the guidelines
- Effective negotiation skills
- Proven ability to influence senior leadership
- Expertise in data architecture concepts such as data modeling, workflow management, ETL/ELT, and real-time streaming)
- Understanding data management and governance concepts such as data quality, metadata, dependency management, etc.
- Ability to communicate effectively with both technical and non-technical stakeholders
- Willingness and ability to learn, adapt and apply new technologies
- Experience with Microsoft Azure/Synapse/Power BI, Epic EHR, or Workday ERP
30. BA in Operations Management with 6 years of Experience
- Strong understanding of IDA, Visual Paradigm
- Strong interpersonal, communication and presentation skills with a good command of written and spoken English
- Experience in defining strategic data architecture in the banking area, e.g., Investment management, Finance, Risk, etc.
- Basic understanding of legal hierarchy representation, product representation, and external data feeds (e.g., D&B, Thomson Reuters, etc.)
- Experience in data modeling
- Strong technical background related to Big Data technologies (Spark, Hive, HBase, Hadoop, Kafka, Flume, Storm, NiFi, etc.)
- Strong technical background related to Data Warehouse/RDBMS in one or more technologies such as Oracle, Teradata, DB2, MSSQL, MySQL
- Strong technical background related to cloud capabilities around the data and associated services
- Knowledge of design tool usage (e.g., EA, Archimate, IDA, Erwin, Visual Paradigm, etc.)
- Knowledge of SDLC/Agile methods
- Good knowledge of MQ, ETL, API Management, and Web Services
- Solid understanding of Enterprise Architecture methodologies, such as TOGAF or others
31. BS in Computer Science with 5 years of Experience
- Deep understanding of the data analytics and data architecture discipline, processes, concepts and best practices
- Strong data design, management and maintenance experience
- Strong experience in data modelling and analytics tools
- Proven strategic planning capabilities
- Strong analytics and reporting experience
- Experience with Machine Learning and Artificial Intelligence
- Excellent understanding of strategic and new and emerging technology trends, and the practical application of existing, new and emerging technologies
- Excellent organizational skills, with the ability to handle multiple and complex areas of responsibility
- Must have strong interpersonal skills
- Excellent analytical skills like technical translator, abstraction, pattern recognition, logical and holistic thinking
32. BS in Information Technology with 8 years of Experience
- Well-versed in the Data domains (Data Warehousing, Analytics, BI, Big Data, Operational Data Store, Metadata, Master Data, Unstructured Data, ETL, ESB)
- Experience with big data technologies such as Hadoop, Hive, Spark, and Kafka
- Ability to build and manage enterprise data and object models, leveraging both industry and application-specific service models
- Experience with unstructured or semi-structured data design and implementation
- Experience with data quality and data profiling tools and processes
- Experience in information technology
- Working experience in the field of Data and Analytics in the area of M&S and CPG industry
- Excellent data architecture and technology knowledge, data engineering skills
- Profound data content knowledge (market data relevant for CPG such as IRI, Nielsen, IQVIA, Kantar, etc., sell-in/sell-out as well as COPA, CRM, and financial data) and M&S process know-how
- Demonstrated ability to achieve stretch goals in a fast-paced environment
- Problem-solving and analytical skills, combined with impeccable business judgment
- Interpersonal and communication skills, active listening, consulting, challenging, and presentation skills
- Fluent in English, both written and spoken
33. BS in Software Engineering with 7 years of Experience
- Experience in Metadata capture, management, cataloging and profiling
- Experience with ETL /ELT technologies
- Experience with catalog data pipeline tools such as AWS Glue
- Experience in implementing data solutions in the cloud
- Knowledge of major cloud-based warehouses such as Snowflake or AWS Redshift
- Experience in leading and mentoring data development teams (BI, Data Integration, Data Quality)
- Experience in leading Data Governance transformations
- Strong knowledge of data-related programming
- Experience with application and middle-tier related programming
- Able to interact with structured and unstructured data and both SQL and NOSQL databases
34. BS in Computer Engineering with 4 years of Experience
- Experience working within a similar IT/Data Architecture role within a global/multinational organization
- Experience with data projects related to the business data lifecycle
- Significant experience in designing and architecting data solutions on a global scale
- Detailed knowledge of infrastructure, database management, applications, or Telecom technologies
- Experienced in decision-making
- Experience in the analysis, implementation, and evaluation of IT systems and their specification
- Understanding of the fundamentals of software development processes and procedures, including the agile approach
- Experience in implementing effective and innovative software development methodologies
35. BS in Information Systems with 6 years of Experience
- Expertise in the design and management of complex data structures and data processes
- Expertise in metadata management, data processing, and reference data management
- Expertise in streaming and batching data processing
- Deep knowledge and hands-on experience in big data and cloud computing technologies
- Strong service architecture and development experience with high performance and scalability
- Experience in defining corporate-wide data strategy and data governance
- Extensive hands-on experience in designing and developing data models, integrating data from multiple sources, data flow design, building data pipelines for a data platform (data lake and data warehouse)
- Experience in SQL, NoSQL, Graph DB, Hadoop and Spark
- Familiar with one or more Architecture Frameworks (e.g., TOGAF, etc.)
- Experience in operating an architecture review board
- Good interpersonal and communication skills
36. BS in Applied Mathematics with 5 years of Experience
- Experience performing logical data modeling and physical data modeling
- Experience in data analysis and data mapping
- Experience creating advanced SQL (multiple joins, subselects, case, decode, and other constructs)
- Experience performing problem analysis and data investigation
- Familiarity with IBM DB2, Cloudant, Mongo and other DBMS
- Experience with Postman or similar API drivers
- Experience in creating, reading and manipulating JSON structures
- Problem-solving, interpersonal, and time management skills to handle high-pressure, complex situations effectively
- Demonstrated communication skills and the ability to work directly with clients/customers
- Highly motivated by team success
37. BS in Management Information Systems with 8 years of Experience
- Previous work in data architecture
- Working experience with event-based, big data and non-traditional architectures
- Ability to build and manage enterprise data and object models, leveraging both industry and application-specific service models
- Experience with large, broadly scoped Data Architecture programs
- Responsible for creating design patterns and best practices for data engineering and the integration of data through the enterprise
- Experience with data catalogs, profiling tools and processes
- Experience with modern event-based data architecture, streaming analytics, Kafka, etc.
- Familiar with training and deployment of AI Machine Learning models and automation
- Experience with data technologies such as Spark and Databricks
- Experience developing enterprise data assets using a variety of traditional and modern data movement and storage technologies
- Graph, document and/or cloud data warehouse experience
- Experienced with API architectures such as web services, ESB, managed API, Apigee
- Ability to lead software evaluations including RFP development, capabilities assessment, formal scoring models, and delivery of executive presentations supporting a final recommendation
- Experience in information technology