Enterprise Data Foundation Data Modeler

Enterprise Data Foundation Data Modeler

Requirements

• Bachelor’s degree required, preference in Computer Science, Data Management/Engineering, Information Systems, Software Engineering or related Technology Discipline.
• 5+ years of overall technology experience that includes at least 2+ years of Data Modeling and Systems Architecture.
• 2+ years of experience with Data Lake Infrastructure, Data Warehousing and Data Analytics tools.
• 2+ years of experience developing enterprise data models.
• 2+ years of experience preparing ‘Source to Target’ data mapping documents and writing data transformation rules.
• 2+ years of experience with data profiling and strong SQL skills with ability to write complex queries. Experience with Python a plus.
• Experience with at least one Data Modeling tool; ER Studio, Hackolade or IDM.
• Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets.
• Experience with at least one MPP database technology; Synapse, Teradata or Snowflake.
• Experience with Master, Transactional, Operational and Reference Data.
• Excellent verbal and written communication and collaboration skills.
• Proficient in Microsoft Office Suite, with a strong focus on Outlook, TEAMs and Excel.

Responsibilities

• Create/modify conceptual, logical and physical data models for any supported platform, including SQL Data Warehouse, Data Bricks, Snowflake, Azure Synapse or other Cloud data warehousing technologies.
• Design physical and logical data models with an extensible philosophy to support future unknown use cases with minimal rework.
• Govern Data Modeling design and advocate for adherence to all approved standards and guidelines.
• Create ‘Source to Target’ data mapping documents, including all appropriate data transformation rules and logic.
• Provide and/or support data analysis, requirements gathering, solution development and design reviews for enhancements to, or new, applications/reporting.
• Assist with data planning, sourcing, collection, profiling and transformation.
• Drive collaborative reviews of design, code, data, security features implementation performed by Data Engineers to ensure accuracy and consistency with data product development.
• Collaborate with IT, Data Engineering, Data Science, Data Governance, and cross-functional teams to ensure the enterprise data model integrates essential dimensions required for effective management of business and financial policies, data security, regulatory compliance at the local level, and privacy-by-design principles—including personally identifiable information (PII) management—all seamlessly connected through core identity foundations.
• Develop a deep understanding of the business domains and enterprise technology inventory to craft a solution roadmap that achieves business objectives and maximizes reuse.
• Expertise with data at all levels: low-latency, relational, unstructured data stores, analytical and data lakes, data streaming (consumption/production) and data in-transit.
• Partner with the Data Governance team to standardize classification of unstructured data into standard structures for data discovery and action by business customers and stakeholders.
• Support assigned project contractors (both on- & off-shore), orienting new contractors to standards, best practices and tools.
• Contribute to project cost estimates, working with senior members of team to evaluate the size and complexity of the changes or new development.

Preferred Qualifications

• Experience with integration of multi cloud services (Azure) with on-premises technologies.
• Experience with data quality tools; Apache Griffin, IDQ and Great Expectations.
• Experience with version control systems; GitHub and deployment & CI tools.
• Experience with Azure Data Factory, Databricks and Azure Machine learning is a plus.
• Experience with metadata management, data lineage, and data glossaries.
• Working knowledge of agile development, including Dev Ops and Data Ops concepts.
• Experience in CPG industry.