Data Governance Data Analyst

Summary

We are seeking a Data Analyst to support the development of trusted, well-understood enterprise data. This role analyzes, maps, profiles, and documents data across source systems, Master Data Management (MDM), the Enterprise Data Warehouse (EDW), analytics, and reporting environments.

You will work across business and technical teams to understand how data is created, structured, related, transformed, and consumed. The work supports data mapping and reconciliation, data quality analysis, technical lineage, business and data requirements, governed data domains, data modeling, and evolving Data Product initiatives.

This role is ideal for someone who is naturally curious and proactive, enjoys investigating data and learning how systems and business processes work, and follows questions across systems and stakeholders to find the underlying answer.

Key Responsibilities

Data Mapping and Lineage

· Analyze and map data across source systems, MDM, EDW, analytics, and reporting environments to understand definitions, relationships, transformations, and usage.

· Develop and maintain source-to-target and field-level mappings. Analyze current- and future-state data flows and trace data through ETL/ELT processes to document upstream sources, transformation points, downstream dependencies, and potential impacts of data changes.

Data Profiling and Quality

· Use SQL to investigate, profile, reconcile, and validate data. Identify discrepancies, anomalies, and potential data quality issues.

· Partner with Data Engineering, BI, and business stakeholders, using Data Governance practices to investigate root causes, assess impacts, and support resolution of data quality and data alignment issues.

Requirements and Governed Data

· Partner with business stakeholders and subject matter experts to understand business processes, terminology, and data usage. Gather and document business and data requirements for technical teams.

· Help establish consistent definitions, mappings, quality expectations, and authoritative sources for governed data domains.

· Contribute to Data Product discovery and development, and to logical and dimensional data modeling as these capabilities mature.

Ownership, Documentation, and Analytics

· Proactively identify gaps in definitions, mappings, requirements, and documentation; determine appropriate next steps and engage the necessary business or technical stakeholders to help resolve them.

· Develop repeatable approaches, standards, and templates for mapping, profiling, analysis, and documentation to improve consistency and reuse.

· Document analytical findings so that discoveries about systems, business rules, mappings, and data relationships become reusable organizational knowledge.

· Create ad hoc analyses and reports as needed to investigate data questions, validate findings, and share results with stakeholders.

Qualifications

· 3 to 5 years of experience in data analysis, data mapping, or business/data analysis, with exposure to data governance practices.

· Experience working with complex enterprise business data, such as ERP, customer, product, order, inventory, supply chain, or similar operational data. Manufacturing experience is preferred.

· Strong hands-on SQL experience to explore, profile, reconcile, and validate data across relational datasets.

· Solid understanding of relational database concepts, including keys, joins, cardinality, and data grain, and how data moves through ETL/ELT into a data warehouse.

· Experience with data mapping, profiling, or reconciliation, and with gathering and documenting business and data requirements.

· Experience with Snowflake or a similar cloud data warehouse platform.

· Understanding of BI, analytics, and reporting principles, including how data models, dimensions, measures, calculations, and business rules support downstream reports, dashboards, and analytical solutions.

· Experience using BI or reporting tools to investigate data and communicate findings is a plus.

· Working knowledge of Python for data analysis, profiling, validation, or automation is a plus.

· Familiarity with master and reference data concepts.

· Familiarity with data governance concepts, including metadata management, data catalogs, lineage, data quality, stewardship, and authoritative data sources.

· Experience supporting Data Products or other governed enterprise data assets.