• Interact with technical as well as purely business-oriented clients, analyze customer data requirements and present proposed solutions, communicate data-related aspects of delivery
• Create data architectures and designs that best fulfill customer requirements
• Lead the implementation efforts
• Oversee data engineers and guarantee the quality of the delivered solutions from the data architecture point of view
• Suggest reusable patterns and process improvements to be implemented across the whole organization
• Follow the trends and newest technologies in data architecture and data methodologies and bring them to practice where appropriate
• Take responsibility for mentoring other engineers
• Build and mentor a world-class team, expanding the impact and reach of data.
• Architect, design, develop and implement enterprise-level data platforms
• Improve the overall scalability and performance of the platform
• Evaluate the current state of the company’s databases and other data systems and identify new solutions to increase efficiency and performance
• Develop database design and architecture documentation for the management and executive teams
• Research new technologies, data modeling methods and information management systems to determine which ones should be incorporated into company data architectures
• Work with cross-functional teams to build new data platforms, and pipelines and support their data needs

Skills: Client Engagement, Data Architecture, Implementation Leadership, Quality Assurance, Process Improvement, Team Mentorship, Data Platform Development, Cross-Functional Collaboration

• Accountability for taking ownership of existing database systems
• Balance short-term wins along with a longer-term vision and roadmap
• Accountability for management of information architecture
• Responsibility for the management of data structure across the business
• Accountability for data fabric performance
• Responsibility for the management of future state roadmaps for information and data infrastructure (multi-year)
• Accountability that information architecture provides business decision-makers with decision-ready information
• Serves as the main source of knowledge for master data, and data quality industry best practices and processes.
• Lead, create and maintain conceptual, logical, and current data state model and analysis for all portfolios, programs, and projects, and review third-party or vendor data models.
• Determine appropriate modeling standards, guidelines, good practices and approved modeling techniques.
• Definition of data interfaces for all portfolios, programs, and projects.
• Ensures data integrity, consolidation, consistency and metadata development in conjunction with data governance.
• Develops data quality assessment approach for master/reference data in conjunction with business stakeholders.

Skills: Database Management, Strategic Roadmapping, Information Architecture, Data Structure Management, Data Fabric Performance, Decision-Ready Information, Data Modeling Standards, Data Quality Governance

• Maintain continuous and up-to-date knowledge of the architecture of the Juice Plus+ enterprise environment.
• Lead and prepare frequent deployments and releases. 
• Ensure that system improvements are successfully implemented.
• Troubleshooting current applications and integration issues.
• Provide Java application software development services and technical support across multiple projects.
• Develop program logic for new Java applications/modify logic in existing applications.
• Code test debug, document implement and maintain software applications and services.
• Analyze requirements, build tests and integrate application components
• Create, build, and consume REST APIs and Microservices.
• Collaborate with technology and business leadership during the whole data lifecycle throughout acquisition, modeling, distribution and reporting
• Work closely with business and technology teams and other partners to understand requirements, assess and prioritize deliverables across the whole Data Analytics portfolio
• Providing leadership, vision, and guidance for developing and maintaining a system-agnostic data architecture relying on industry standards
• Emphasize the risks and benefits of various architectural solutions
• Defining standards for data gathering, storage, quality, transformation, integration and consumption

Skills: Enterprise Architecture, Deployment Management, System Improvement, Application Troubleshooting, Java Development, API Development, Data Collaboration, Data Architecture

• Play a role in bringing autonomous technologies to the real world. 
• Help engineer and generate data-driven insights into system performance (spanning hardware, software, and services) as well as synthesize critical data for engineers and leadership across the program.
• Develop data models for utilizing the rich data involved in creating an autonomous system
• Build and scale data pipelines for a large, multifaceted organization
• Build an understanding of the variety of domains required to build an autonomous system, and provide clear frameworks for connecting each domain’s data into a complete picture
• Create visualizations to help users understand the available data
• Synthesize large, unstructured data into clear and broadly usable datasets
• Expand and deliver a BigData roadmap
• Provide insight and improvement around data governance, resilience and recovery
• Design, build and support a robust and scalable data warehouse.
• Create and maintain documentation detailing and supporting all data warehouse processes.
• Work with BI Analysts and stakeholders to identify, develop, implement and support projects to build and enhance the data warehouse.
• Work in a fast-paced environment managing multiple active projects with different stakeholders to successful conclusions.

Skills: Autonomous Technology Integration, Data Modeling, Data Pipeline Development, Domain Knowledge Integration, Data Visualization, Data Synthesis, Big Data Roadmap Development, Data Warehouse Management

• Provide leadership and support for the development of an integrated Customer Experience data foundation in the Snowflake environment that will enable extensive business intelligence and machine learning for the CX Platform and extended user communities.
• Work with CX business and IT teams to ensure high-quality, on-time deliverables that meet usability, scalability, quality and performance standards.
• Run technical and business planning workshops, help build Centers of Excellence, and perform adoption planning and maturity assessments.
• Apply a variety of big data technologies to ingest, transform, index, aggregate, correlate, provide APIs, visualize and enable a spectrum of organizations across Cisco.
• Analyze structural requirements for new data storage solutions and applications
• Design architectures for technical systems (Snowflake & Google Cloud) to ensure robustness, scalability, and completeness
• Provide admin-level support for Snowflake and Google Cloud Platform
• Mentor other team members to guide them throughout their onboarding
• Development and maintenance of the data architecture guiding principles, policies, best practices, and standards
• Improve system performance by conducting tests, troubleshooting and integrating new elements.
• Design data models for optimal storage and retrieval and optimize the data architecture to meet critical product and business requirements.
• Establish architectural approaches and patterns that incorporate modernizing data governance, metadata management and data quality.
• Identify and recommend the appropriate data management toolset for managing master data and predictive data management.

Skills: CX Data Leadership, Project Management, Workshop Facilitation, Big Data Application, Storage Analysis, System Architecture, Snowflake Admin, Data Governance

• Design and implement effective data platform solutions (databases, data lakes, data warehouses) and models to store and retrieve company data.
• Design and implement data ingestion pipelines (ETL/ELT) in Azure environment
• Design and implement platform and data quality monitoring solutions
• Examine and identify database structural necessities by evaluating client operations, applications, and programming.
• Assess database implementation procedures to ensure they comply with internal and external regulations.
• Prepare accurate database design and architecture reports for management and executive teams.
• Oversee the migration of data from legacy systems to new solutions.
• Educate staff members through training and individual support.
• Communicate with many different company stakeholders to assess needs and goals
• Evaluate current data architecture and databases
• Apply ETL (extract, transform, load) best practices and design patterns in the creation of data ingestion pipelines
• Research and discover new methods to acquire and process data
• Preserve a repository of all data architecture artifacts

Skills: Data Platform Design, ETL Pipeline Development, Data Quality Monitoring, Database Evaluation, Compliance Assessment, Database Reporting, Data Migration Management, Staff Training

• Design, develop and lead platform features
• Collaborate with ML Engineers, Backend Engineers and Products Managers to deliver new Platform capability
• Define security and backup procedures
• Monitoring database efficiency and recommending indexing best practices and memory/disk space optimization
• Participate in early customer engagements and POCs, and use that context to drive new product features
• Review design and code, and make sure what we ship is awesome
• Ensure data infrastructure offers reliable high-quality data with consistent SLAs with good monitoring, alerting and incident response and continual investment to reduce tech-debt
• Improve system performance by conducting tests, troubleshooting, and integrating new elements
• Interface with clients, vendors, and internal users of the data platform to understand the data
• Work closely with the business to identify and specify opportunities for integration with existing systems in a highly resilient manner
• Contributes to knowledge base
• Works with the data engineering team to identify platform enhancements for increased supportability and reliability
• Architecture design and research on data product lines, developing the system's overall technical framework, business framework, and system framework.
• Creating collateral to articulate the strategy of complex concepts into simple solutions

Skills: Feature Development, Cross-Functional Collaboration, Security Procedures, Database Monitoring, Customer Engagement, Code Review, Data Reliability, Performance Improvement

• Define enterprise data architecture to meet the overall needs of business and set technical vision for data architecture
• Define the data architecture roadmap
• Ensure compliance and follow up on data consumption needs with all business stakeholders
• Maintain business information model and data flow architecture
• Ensure compliance with the Company’s Data Model (participation in solution reviews, development of solution-specific models,..)
• Define standards for metadata, data administration and data lineage tracking together with the data governance team
• Create processes for Data Life Cycle management together with the data governance team.
• Translating complex business and technical challenges into logical data models
• Support and/or advisory on data architecture and product design to digital projects across the business areas.
• Be a driver for data architecture and data management as disciplines in Equinor.
• Work and collaborate closely with enterprise architects, data scientists and software engineers.
• Develop the data architecture competency in the organization, and participate in the Data architect network.
• Be a part of the Enterprise Data Management data product support team.

Skills: Enterprise Data Architecture, Data Architecture Roadmap, Stakeholder Compliance, Information Modeling, Metadata Standards, Data Life Cycle Management, Logical Data Modeling, Cross-Disciplinary Collaboration

• Serve as liaison between data consumer representatives and data or application solution development teams
• Define techniques, guidelines and best practices for data management
• Maintain current state, define the target state of the enterprise data architecture
• Identify the gaps between the target and the current state of data architecture and together with other IT specialists develop a roadmap toward the target state
• Together with the DBA team, system administrators, application developers and analysts establish and manage the metadata management approach and identify metadata assets
• Develop a corporate data dictionary, including data flow diagrams, current data classification and security levels
• Participate in all data management initiatives, take part in determining information requirements for new projects and/or change requests
• Assist in identifying the information elements that already exist in the enterprise data architecture, or need to be added
• Work in cooperation with the data modeling staff (DB administrators, application developers) concerning the creation of all physical and logical data models
• Participate in data integration, data exchange, BI and content management teams to ensure the reuse and consistency of information assets
• Participate in due diligence for new SW purchases by reviewing the data models contained in the applications
• Participate in developing the data objects and data models to support data services under the SOA approach
• Stay up to date with IS requirements, regulatory guidelines (such as privacy requirements), compliance guidelines (such as data retention requirements) and industry standards related to corporate data
• Design solution and data architecture during the project lifecycle in cooperation with the Chief IT architect and other data and solution architects.

Skills: Data Liaison, Data Management Best Practices, Current and Target State Architecture, Gap Analysis, Metadata Management, Corporate Data Dictionary, Information Requirements Analysis, Data Model Collaboration

• Collection, cataloguing and analysis of data requirements.
• Development of conceptual and logical data models to represent and communicate data requirements and to enable understanding of data assets.
• Design of system data and information flows.
• Management of data requirements and models.
• Advising on data transformation from one format or medium to another.
• Providing SME knowledge and experience of healthcare informatics best practices.
• Creating architecture for systems processing large and unstructured datasets (Data Lake Architecture, Streaming Architecture)
• Designing modern DWH/Big Data solutions in the cloud and the Continuous Delivery/Continuous Integration environment
• Designing data models and documenting data flow in the system
• Working with the Team as a Technical Leader, ensuring system compliance with current standards and best practices in software development.
• Establishing data architecture artifacts and data management standards and guidelines for Group Risk and Group Finance based on Group policies and instructions.
• Contributing by describing and advising how data should be organized and managed by delivering logical data models, data specifications, data definitions, and data flows.
• Work with data catalog and help recognize data as an asset.

Skills: Data Requirement Analysis, Data Modeling, System Data Flow Design, Data Management, Data Transformation Advisory, Healthcare Informatics Expertise, Data Lake Architecture, Cloud DWH Solutions

• Progressive experience in Enterprise IT environments, including in data analytics.
• Technical architecture experience
• Deep knowledge of Microsoft Azure data analytics tool stack including practical project experience.
• Deep knowledge of RDMS principles.
• Experience in data warehouse/lake design and development including ETL/ELT processes and tuning
• Significant experience with data modeling
• Knowledge of data governance, metadata management, data access/security, build-out and maintenance of a data catalog.
• Knowledge of data architecture and design patterns and the ability to apply them.
• Conceptual understanding of data transport techniques. 
• Previous experience in the creation of data transport
• Ability to work with multiple source data technologies to create overarching data architecture.
• General technical knowledge of IT development to inform understanding of the feasibility of the architecture. 

Qualifications: BS in Computer Science with 12 years of Experience

• Experience with data architecture strategy, design, and development.
• Experience with data management activities and concepts including an understanding of best practices for enterprise data modeling and management.
• Experience designing complex integrations with a focus on data modeling and data engineering.
• Experience in data governance capabilities, policy, process, and procedures.
• Strong time and priority management ability.
• Excellent problem-solving/analytical abilities.
• Solid verbal, written, and listening communication skills.
• Demonstrate the ability to work independently with minimal supervision.
• Experience working in a Scrum-Agile environment.
• Exposure to the Workday suite of applications/modules.

Qualifications: BS in Information Technology with 7 years of Experience

• Hands-on experience in designing, implementing and operating large-scale data & analytics solutions with experience in data architect roles.
• Good understanding of technology trends and the practical application of existing, new and emerging technologies to enable new and evolving business and operating models.
• In-depth knowledge of and experience with modern data management technologies (e.g., SQL/NoSQL Database, Data Warehouse, Distributed Data Storage like Apache Hadoop, MDM)
• In-depth knowledge of and experience with data engineering technologies (e.g., ETL/ELT, Streaming/Apache Kafka, MapReduce, Apache Spark, Apache Flink)
• In-depth knowledge of and experience with analytics & BI technologies (e.g., Power BI, Tableau, FineBI, Qlik)
• Hands-on experience in cloud technologies (e.g., Azure, AWS, AliCloud), and network and security technologies
• Experience in Data Science and Advanced Analytic tools (e.g. Python, R)
• Excellent communication and interpersonal skills, including the capacity to articulate the case for IT investments and alternatives in the language of business.
• Demonstrate successful records of rapidly building relationships with key stakeholders.
• A motivated, self-directed, highly proactive attitude and approach.
• Strong communication skills in both written and verbal English.

Qualifications: BS in Data Science with 10 years of Experience

• Technical background in healthcare, laboratory diagnostics, medical devices, or pharmaceutical companies.
• Proven ability to innovate with a history of new or improved technology solutions with remarkable impact on company productivity.
• Demonstrate the ability to influence others in areas of science and technology.
• Extensive hands-on technical proficiency in SQL, NoSQL, knowledge graphs, data warehousing, and data modeling experience.
• Metadata management, data quality, master data, and data lineage experience
• Petabyte-scale data platforms experience
• Highly regulated and restricted data domains experience
• End-to-end data lifecycle management, including reporting solutions, dashboards, business intelligence, or other user-facing information delivery experience
• Developing scalable solutions on cloud infrastructure experience
• Statistics and data science expertise familiarity
• Familiarity with a variety of programming languages, including Python
• Agile/DevOps experience

Qualifications: BS in Software Engineering with 14 years of Experience

• Experience as a Data Architect, Data Engineer, Data Scientist or similar role
• In-depth understanding of database structure principles
• Expertise in SQL and Data warehousing concepts
• Familiarity with data visualization tools (e.g. Tableau)
• Enterprise SaaS experience preferred
• Experience with AWS, Redshift or Snowflake
• A firm believer in data-driven decision-making
• Great organization skills with the ability to manage competing priorities
• Proven analytical skills with attention to detail
• Self-driven with the ability to work in a self-guided manner with strong problem-solving skills

Qualifications: BA in Information Systems with 6 years of Experience

• Experience in data architecture, metadata architecture, metamodels and major data governance initiatives focusing on advancing curated, high-quality enterprise data sets.
• Experience in data modeling and building conceptual, logical & physical models, and related tools such as ER/Studio, Erwin, Hackolade
• Experience with relational, NoSQL, and Big Data storage solutions and requirements
• Experience with ontologies, RDF/OWL, SHACL, Knowledge Graphs, and related tools (Top Quadrant, Protégé)
• Deep understanding of and experience with Data Governance tools such as Collibra, Alation, Manta
• Experience with identifying and tagging sensitive data through automated solutions
• Experience working in financial services
• Solid understanding of Data Management and Data Governance concepts 
• The ability to be an advocate for architecture that supports Amex’s governance/management of data.
• Excellent communication skills with a demonstrated ability to engage, influence, and encourage partners and stakeholders to drive collaboration and alignment.

Qualifications: BS in Computer Engineering with 7 years of Experience

• Experience in performing data analysis and assessments of data integration sources
• Strong SQL skills against industry standard DBMS (IBM, DB2, Oracle, SQL Server)
• Experience using an SQL Management tool such as Toad, Rapid Query, or Tora
• Experience in data modeling, data mining and segmentation techniques
• Experience with Collecting and Analyzing Business Requirements and Process Designs
• Experience using statistical packages for analyzing datasets – Excel, SPSS, or SAS
• Conduct quality assurance of integrated data supporting initiatives for data integrity and normalization
• Ability to identify data disparity and complete research for root cause identification
• Ability to drive data standardization and quality measurements based on analysis outcomes
• Knowledge of IT Service Management, ITIL principles (Specifically, IT Asset and Configuration Management)

Qualifications: BA in Database Management with 8 years of Experience

• Hands-on experience in Data Science and/or Data Modeling
• Financial industry knowledge in lending, risk management, servicing and risk/regulatory reporting
• Product knowledge in commercial banking, capital and investment banking and markets
• Extensive experience in UML/relational/hierarchical/ /Big Data concepts
• Hands-on modeling expertise using Magic Draw, Erwin or Enterprise Architect and metadata management tools
• Data modeling experience using Magic Draw and Cameo. 
• Able to utilize Code Engineering Sets to generate executable code or a database script. 
• Knowledge of Data Management methodologies involving architecture, modeling, storage, security
• Prior experience in data integration, interoperability and data quality solutions.
• Analytical and problem solver, excellent verbal, written and presentation skills

Qualifications: BA in Business Analytics with 5 years of Experience

• Experience in designing and delivering service-based cloud platforms or sophisticated enterprise-level systems
• Must have experience in various data model patterns used in different data architectures.
• Experience producing various architectural artifacts and presenting them to various stakeholders and review boards.
• Proven ability to work across structured, semi-structured, and unstructured data, extracting information and identifying linkages across disparate data sets
• Strong experience in multiple database technologies such as Distributed Processing (Spark, Hadoop, EMR), Traditional RDBMS (MS SQL Server, Oracle, MySQL, PostgreSQL), MPP (Azure Synapse, Azure Data Factory)
• Data modeling principles including conceptual, logical and physical data modeling, dimensional modeling techniques
• Experience in data warehouse architectures (e.g. Azure Synapse DB and Enterprise BI)
• Practical experience in data mining and analysis tools with intermediate to advanced query skills (ex. MS SQL, Synapse Analytics, Data Explorer, Cosmos).
• Ability to learn quickly and identify opportunities for improvement.
• Experience with understanding technical design specifications that are consumed by development/engineering teams as a guide for implementation.
• Strong understanding of Information Security principles to ensure compliant handling and management of data

Qualifications: BS in Computer Science with 9 years of Experience

• Expertise experience in using and implementing processes and tooling associated with continuous integration, delivery and deployment of software solutions.
• Expertise experience in technical design and development of data, reporting and/or analytics systems.
• Expertise experience in data integration and transformation solutions, e.g. Talend, Informatica, Matillion, Segment, Fivetran, SnapLogic, Stitch, Apache Kafka, AWS Lambda, etc.
• Expertise experience in relational and graph data warehouse solutions, cloud data warehouse
• Expertise experience in SQL and knowledge of data engineering languages, and ability to review code.
• Experience in master data management discipline, strong knowledge of master data management solutions
• Experience in business intelligence and reporting tools and capabilities, e.g. SAP Suite, Google or Adobe Analytics, Microstrategy, IBM Suite, Oracle Suite, Power BI, etc.
• Extremely organized and strong knowledge of project management, team collaboration and documentation software, e.g. Atlassian Jira, Confluence, Trello, Slack, etc.
• Thought leader with deep analytical skills who can ask relevant questions at the right time and provide multiple solution approaches to problems and challenges related to architecture, technical and non-technical issues.
• Demonstrate initiative to stay abreast of technology advancements.
• Ability to apply technology in solving business technical problems.
• Knowledge of systems architecture technology, principles, methods, tools, practices and industry standards.

Qualifications: BS in Information Technology with 17 years of Experience