Enterprise Data Architect Skills, Experience, and Job Requirements

ENTERPRISE DATA ARCHITECT SKILLS, EXPERIENCE, AND JOB REQUIREMENTS

Published: Feb 05, 2025 - The Enterprise Data Architect excels in managing enterprise information, ensuring data consistency, quality, and availability across the organization. Skilled in defining Data Strategy, Governance processes, and integrating diverse applications through robust data architecture. Strong leadership, communication, and mentoring abilities to drive strategic and tactical data initiatives.

Essential Hard and Soft Skills for a Standout Enterprise Data Architect Resume

Data Architecture Design
Data Governance
Data Modeling
Cloud and Data Platform Design
Data Integration
Data Management Strategy
Business Requirement Translation
API Architecture
Data Services Design
Data Quality

Business and IT Collaboration
Mentorship and Education
Stakeholder Engagement
Team Mentoring
Project Management
Presentation
Best Practices Implementation
Thought Leadership
Collaborative Leadership
Industry Engagement

Summary of Enterprise Data Architect Knowledge and Qualifications on Resume

1. BA in Statistics with 9 Years of Experience

Professional technology experience with a concentration in data.
Superior knowledge with the ability to manage and coordinate enterprise information use, corporate data access design, metadata management and distributed/replicated data approach to ensure consistency, timeliness, data lineage, data quality and availability of master data throughout the enterprise.
Ability to define Data Strategy, Data Governance processes.
Prior experience in defining Data Strategy
Hands-on experience with one or more business intelligence tools or comparable programming and data experience
Ability to create various levels of data architecture and data architecture constructs such as transactional, operational and analytical data stores to facilitate the integration of a diverse set of applications built upon disparate technologies
Ability to envision and balance strategic, long-term data needs for the enterprise while coordinating and aligning multiple short-term tactical priorities with the ability to implement change in a complex dynamic environment.
Demonstrated strong leadership and mentoring skills with a broad technology background combined with the ability to build relationships with business and technology stakeholders.
Strong understanding of data from an enterprise perspective with expertise in developing strategic and tactical data technology direction.
Ability to teach, lecture, tutor, coach, formally or informally in one own area of expertise.
Excellent verbal and written communication and facilitator skills.
Experience in insurance will set a candidate apart from others.
Strong understanding of SDLC methodology.

2. BA in Applied Mathematics with 11 Years of Experience

Proven experience in a complex configurable products business environment, preferably in multiple business domains (Innovation/RandD, Supply chain, Manufacturing, Customer Service), where experience with PLM
Proven experience with data modeling techniques
Experience with SAP (S/4HANA) and additional experience with Siemens Team Centre
Experience in a data management role
Experience in a leadership role in a multi-year business transformation program
Experience in working in an Agile IT environment
Demonstrate flexibility and pragmatism, while maintaining the highest standards of quality for own and other people’s work
Able to build effective virtual teams
Able to deal with resistance
Effective communication skills and proficiency in the English language
Capable of switching between classical PMM methodology and Agile approach
Experience in applied expertise in Data Architecture and Software Engineering methodologies across OLTP and OLAP systems
Experience in data analysis, data modeling, data profiling, and data optimization of structured and unstructured data
Strong understanding of data management and data quality concepts
Advanced knowledge of industry best practices in the various aspects of information, technology trends, enterprise operations knowledge and the ability to develop solutions
Ability to concisely and clearly articulate ideas, while influencing others through collaboration
Experience working in applications, integrations, and/or data warehouses executing system changes to support new business processes and business process changes, understanding

3. BA in Management Information Systems with 11 Years of Experience

Hands-on experience working in enterprise-scale data warehousing, data architecture, and/or data engineering environments.
Experience in working as an Enterprise Architect with a good understanding of Enterprise Architecture as a practice.
Practitioner’s knowledge of TOGAF or alternate frameworks
SQL (HANA, Snowflake, Oracle, AWS Redshift, Databricks, Hive etc.) experience
Hands-on data modeling experience, especially dimensional data modeling
Must have knowledge of Tableau, Qlik or other Data visualization tools
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, metadata management.
Experience managing, measuring, improving data quality in a data warehouse.
Communication skills including the ability to identify and communicate data-driven insights
Experience as an enterprise data architect, with in-depth knowledge of and able to consult on various technologies and industry best practices around data architecture in both cloud-based and on-prem solutions
Experience in end-to-end implementation of data intensive analytics-based initiatives, with a comprehensive understanding of data warehousing and data transformation (extract, transform and load) processes and the supporting technologies such as Azure Data Factory, Data Lake, other analytics products
Excellent problem solving and data modelling skills (logical, physical, semantic and integration models) including normalisation, OLAP / OLTP principles and entity relationship analysis
Experience in mapping key enterprise data entities to business capabilities and applications supported by a strong knowledge of data lineage from source to output
An understanding of big data architectures and emerging trends, with strong analytical and numerical skills which support easy interpretation and analysis of large volumes of data

4. BA in Business Analytics with 10 Years of Experience

Demonstrated ability to develop architectural models and roadmaps aligned with business capabilities and strategy
Expert logical analysis and conceptualization skills
Strong leadership, with the ability and courage to make sound decisions and drive change across the enterprise
Deep knowledge of architectural patterns – such as data warehouse, data lake, and data hub – and the ability to leverage them to enable operational and analytical use cases
Familiarity with data architecture concepts, including master data management, data curation, ETL/ELT, data pipelines and data security best practices
Ability to identify fit for purpose data stores (relational, NoSQL, document, graph, etc.) to meet business requirements
Experience with distributed data and analytics architectures in cloud and hybrid environments
Experience managing structured and unstructured data at scale
Understanding of system integration and data access approaches, such as APIs and event-based architectures
Strong business acumen and experience developing business cases
Excellent oral and written communication skills to effectively deliver messages to a wide range of audiences - from executive to technical
Innovative and strategic mindset
Strong teamwork and interpersonal skills, with the ability to deliver results working independently or in a collaborative environment
Experience in technology leadership, including a data-related architecture role
Financial services industry experience
Familiarity with business intelligence tools, such as Tableau or Microsoft Power BI
Data modeling expertise at the enterprise level, including canonical modeling

5. BA in Software Engineering with 12 Years of Experience

Design, implementation, consulting, pre-sales experience with regulated environments.
Experience in Data, Database and ETL development, support and operations using IBM Data Stage/ Microsoft SQL Server/ MDS with emphasis on Data quality.
Deep understanding of master data importance (including data model and attribute level information) in SAP and ability to guide the client resources while establishing the data governance organization.
Experience leading complex SAP projects working with cross-functional teams of Business, IT, and Compliance teams
Experience developing and reviewing SAP configuration for master data (both ECC and MDG) using SAP implementation guide.
Implementation experience with SAP Enterprise Information Management technologies such as SAP S/4MDG, Data Services, and Information Steward.
Implementation experience with Informatica MDM and/or Talend MDM.
Exposure to and conceptual understanding of data integration tools and technologies
Troubleshooting and analytical skills.
Good communication and collaboration skills.
Client management skills.
Experience leading, guiding and contributing to Informatica MDM/Talend MDM/SAP MDG efforts around governance, blueprinting and implementations.
Sound experience working with Customer and Vendor master data in the context of SAP ERP.
Knowledge and hands-on experience with Informatica MDM/Talend MDM/SAP MDG (Master Data Governance) Architecture and development.
Solid conceptual knowledge around Data Management, data quality and data governance.
Certifications such as SAP Certifications or Data Management certifications

6. BA in Data Science with 4 Years of Experience

Strong experience in normalized relational data modeling
Strong experience in analytical data modeling
Strong experience in data management within a big data store, both OLTP and OLAP
Experience in non-relational databases (NoSQL, time series)
Strong communication and teamwork skills
Experience in ETL tools, message queues, and other forms of data movement.
Strong demonstrable experience delivering complex solution architecture for enterprise scale solutions in public cloud and hybrid eco-systems.
Must have in-depth understand and experience in two or more of the following: public cloud computing, data lakes, Big Data transformations and analytics, complex e-commerce applications, IoT edge and cloud data processing, SQL and NoSQL data design.
Strong understanding of Agile SDLC implementation in public cloud eco-system including environments management, test automation, peer review, CI/CD, resource optimization, etc.
Must have excellent communication skills and be able to deal with sensitive issues, mentor and coach and/or persuade others on new technologies, new applications, or potential solutions.
Multiple experiences as data architect with working knowledge of data management, data lake, data warehouse, data governance, BI and analytics.
Experience in establishing standard data processes to acquire, analyze, store, cleanse, and transform large datasets.
Understanding of metamodels, taxonomies and ontologies, as well as the challenges of applying structured techniques (data modeling) to less-structured sources.
Architecture experience and background in information systems and information technology
Experience in data architecture with increasing responsibilities in modern data architecture practices, leveraging

7. BA in Information Systems with 7 Years of Experience

Experience working in the full life cycle of data architecture projects i.e. discovery, design, development and implementation
Fluent and current on architecture trends with an eye on market/technical conditions and future direction
Direct experience with Data Warehouse, ETL, Data Quality, Master Data Management is mandatory
Prior experience with defining Data Models from scratch is critical
Direct experience working with AWS/Azure technologies (namely Data Lake, No-SQL Database and Data related Services)
Direct experience with utilizing data modeling tools
Familiarity with cloud-based data processing platforms (namely Apache Storm, Spark, Kafka, Flink etc)
Deep understanding of the usages of Star and Snowflake schemas to model warehouses
A good understanding of data security skills
Excellent written and oral communication skills
Ability to communicate effectively with both technical and business stakeholders
Experience working with large data sets and distributed computing tools
Experience in Agile methodology and relational database design principles
Ability to elicit requirements and communicate clearly with non-technical individuals, development teams, and other ancillary project members
Experience with AWS and/or Azure Services related to Data and Data Management
Experience in Healthcare and Healthcare IT Industry is critical
Experience with Electronic Health Records (EHR) systems and protecting patient information in compliance with the Health Insurance Portability and Accountability Act (HIPAA)

8. BA in Computer Science with 9 Years of Experience

Experience with owning and implementing all facets of Data pipeline & Architecture bridging the needs of Analytics with Engineering solutions.
Experience with Cloud Technologies (E.g., AWS, GCP, etc) including a track record of learning new technologies and architecting them to solve business problems
Experience building and scaling data products and machine learning models
Experience building and scaling BI tools and associated workloads to produce reports to meet data analysts and business expectations on timing & quality
Experience in mentoring junior team members through code reviews and recommending adherence to best practices.
Deep understanding of writing and automating test cases to ensure data quality, reliability (including monitoring & alerting), and a high level of confidence.
Passionate about improving the quality, efficiency, reliability, and scalability of data systems.
Financial services industry experience
Experienced in establishing standard data processes to acquire, analyze, store, cleanse, and transform large datasets.
A deep understanding of metamodels, taxonomies, and ontologies, as well as the challenges of applying structured techniques (data modeling) to less-structured sources.
Architecture experience and background in information systems and information technology, with at least in data architecture with increasing responsibilities in modern data architecture practices, leveraging the majority of the following technologies/platforms
Cloud platforms experience on major public cloud technologies - Azure, GCP and AWS
Data ingestion, processing, transformation, and integration technologies
Understand the long-term ("big picture") and short-term perspectives
Communicate very effectively to executives, senior business, and technology leaders.

9. BA in Statistics with 10 Years of Experience

Experience with owning and implementing all facets of Data pipeline and Architecture bridging the needs of Analytics with Engineering solutions.
Experience with Cloud Technologies (E.g., AwS, GCP etc) including track record of learning new technologies and architecting them to solve business problems
Experience building and scaling data products and machine learning models
Experience building and scaling BI tools and associated workloads to produce reports to meet data analysts and business expectations on timing and quality
Experience in mentoring junior team members through code reviews and recommend adherence to best practices.
Deep understanding of writing and automating test cases to ensure data quality, reliability (including monitoring and alerting) and high level of confidence.
Passionate about improving quality, efficiency, reliability and scalability of data systems.
Financial services industry experience
Development experience building and maintaining ETL pipelines, database systems (schema definition, data modeling etc).
Python development experience.
Expert skills working with SQL queries, including performance tuning, utilizing indexes, and materialized views to improve query performance.
Advanced knowledge of both OLTP and OLAP environments with successful implementation of efficient design concepts.
Proficiency with the design and execution of NoSQL database to optimize BigData storage and retrieval.
Experience with API code integrations with external vendors to push/pull data between organizations.
Familiarity with data orchestration pipeline using Argo or Airflow.
Knowledge of analytic tools such as R, Tableau, Plotly, Python Pandas.

10. BA in Applied Mathematics with 8 Years of Experience

Proven experience in data architecture and data modeling.
Strong track record to produce and read data models from conceptual to logical.
Experience in dimensional data, star schema and Data Vault 2.0 modeling.
Experience in using data modeling tools WhereScape 3D, PowerDesigner.
Experience in using data integration solution WhereScape RED
Good knowledge in database management, a plus if on SnowFlake.
Be familiar with master data and reference data concepts and management
Experienced to work in SCRUM methodology or following an agile approach
Experience in MDM platform implementation such as SAP-MDG
Experience in defining data governance processes and building a data dictionary platform such as Collibra.
Experience to work with SAFe methodology
Knowledge about BI and Big DATA ecosystems (S3, Scala, Spark)
Very good communication skills and strong ability to engage at different levels in the organization.
Highly collaborative mindset.
Fluent in English.

11. BA in Management Information Systems with 5 Years of Experience

Must have experience implementing and integrating with ERP (SAP) and fulfillment solutions.
Must have experience with Omni-channel Order fulfillment solution deployments.
Must have experience designing/implementing microservice architecture.
Must have experience in designing and implementing highly scalable web services on cloud.
Experience with Domain Driven Design and SAFe is highly desirable.
Excellent verbal and written communication and collaboration skills to effectively communicate with both business and technical teams.
Experience with SAP S4, Sales and Distribution, Master Data (SAP MDG).
Strong experience with Cloud Computing, DevOps, Java, JavaScript, Angular, REST API, noSQL DB
Self-starter with high motivation and passion to thrive and adopt in an ever-changing, fast-paced environment.

12. BA in Business Analytics with 14 Years of Experience

Expert level development skills in SQL and at least one other database language (Cassandra, Columnar, OLAP)
Experience managing multi-tenant data models
Experience using schema migration technologies (Alembic, Rails Migrations, etc.)
Strong knowledge of relational databases and data modeling (MSSQL and Postgres)
Familiarity with alternative data storage technologies (S3, MongoDb, Redis, Neo4j)
Experience various data modeling approaches (eg stars schema, Type 2, snapshots, schemaless)
Experience with the warts of clinical and financial healthcare data will help (a lot)
Data Architecture experience.
Demonstrated data modeling experience including conceptual, logical and physical in delivering a single view of customer and MDM.
Demonstrated data architecture and data management delivery experience, along with a highly inquisitive approach to business problem solving.
Knowledge of relational and NoSQL databases (Oracle, DB2, SQL Server and MongoDB)
Experience in working with stakeholders to deliver effective change within the data management space.
Good communication skills, stakeholder management skills, change management skills and ability to work in a team.

13. BA in Software Engineering with 15 Years of Experience

Experience in a large complex data ecosystem, domain expertise with complex high-tech manufacturing environments
Experience in building cloud-native architectures in support of digitization and Industry 4.0 initiatives.
Experience with Microsoft Azure (ADLS, Synapse, IoT Hub, Data Factory etc.)
Experience with working with data from multiple sources and formats, architect the corporate core data element layer
Excellent verbal and written communication skills, strong ability to influence on the executive level while having retained technical edge (not a PowerPoint architect position)
Demonstrated ability developing and delivering corporate level data strategies and roadmaps
Experience with Agile delivery models, has successfully led diverse distributed teams
Strong command of the other aspects of corporate data management
Experience in IoT
Experience in the semiconductor industry
Strong attention to detail, problem-solving skills, and verbal/written communication, including communicating updates, risks, etc.
Work in a fast-paced, dynamic global team environment.
Ability to conceptualize, design, and develop information technology architecture(s) to support company requirements.
Broad knowledge of information technologies, technology integration strategies, databases, application/infrastructure patterns, and data warehousing.
Understanding of legacy system migration strategies, methodologies and toolsets.
Experienced with building and managing vendor relationships.

14. BA in Data Science with 12 Years of Experience

Experience in creating, communicating, and implementing scalable enterprise data models
A track record of working with business partners to extract data modeling requirements from business needs
Experience in architecting and implementing Enterprise Big Data solutions
Experience in relational and non-relational data models
Experience in data profiling and mapping
Experience in AWS and Azure cloud platforms and technology
Experience with a data modeling tool such as Navicat, ER/Studio, Erwin, PowerDesigner, etc
Familiarity with Data as a Service concepts
Strong communication skills with ability to communicate with technical and non-technical stakeholders
Independent, motivated, critical thinker and strong self-learner
Ability to think big and challenge conventional wisdom regarding technology.
Ability to build, inspire, and lead cross-functional teams of various sizes.
Excellent communication and documentation skills.
Self-motivated with the ability to work in ambiguous environments with limited day-to-day supervision.
Data warehouse experience and SQL experience
Experience in application and data architecture and solution design
Experience with relational databases such as SQL server, Oracle, DB2, or Teradata

15. BA in Information Systems with 10 Years of Experience

Experience with large-scale, distributed data pipelines, as well as data management, modeling, and storage
Experience building large scale data processing and analytical systems
Proven understanding of data governance, data quality, reusable frameworks and decision support systems design principles
Deep understanding of modern data engineering practices including scalability, distributed computing, AWS cloud infrastructure, containerization, etc.
Demonstrated experience in architecting and implementing Data Warehouse, preferably using Snowflake
Proven ability to inspire confidence, create executive presentations and guide strategic discussions with senior management.
Ability to understand and adapt to changing business priorities and technology advancements
Ability to operate in a multifaceted and fast-paced environment, building strategy while executing tactics, including hands-on contributions
Proven track record of collaboration with engineering leaders and business partners to drive impact
In-depth, hands-on experience using structured and unstructured data as well as key data technologies, including AWS, Snowflake, EMR, Airflow, Hive, Kinesis, Spark, etc.
Background in all aspects of software engineering with strong skills in parallel data processing, data flows, REST APIs, JSON, XML, and microservice architecture
Experience working in a scrum/agile environment and associated tools (Jira)
Excellent written and verbal communication skills
Data modeling experience
Ability to translate business questions to technical specifications.

16. BA in Computer Science with 11 Years of Experience

Data modeling experience working with at least three various types of data models (RDBMS, NoSQL, Graph, Columnar, Document) and developing solutions for multiple cloud-based data platforms
Complex enterprise experience leading distributed data architecture efforts with subject matter authorities from varying technology and business disciplines
Experience in Domain-Driven Design, SOA, Data Management, Data Services and Platforms
Experience architecting scalable, highly available, robust, cloud centric technical solutions
Broad knowledge of Web technologies: languages, frameworks, techniques, industry trends, etc.
Enterprise-wide awareness of the business and data domains in relation to core business processes and capabilities, and enabling technology platforms
Experience designing and/or optimizing processes to ensure operational excellence
Applying architectural principles and government based on established principles
Strong architecture, critical thinking, and problem-solving abilities, along with an ability to handle ambiguous, and evolving requirements
Experience successfully planning, influencing, and leading architecture initiatives across IT and business organizations and teams
Outstanding interpersonal skills with the ability to communicate effectively with all levels in the company, this includes written and verbal communications as well as visualizations
Ability to navigate and work effectively across the organization to influence, inspire and lead others around decisions that provide clear positive results to the company
Strong data modeling skills.
Good understanding and experience in building star schema and denormalized data structures.
Report authoring experience and experience implementing ETL.
Working knowledge of reporting tools like Tableau, Looker, SSRS, Business Objects etc.
Strong SQL skills, ideally experienced with Google Big Query

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