Key Responsibilities:
- Manage Project Delivery: Lead end-to-end data projects from planning to launch using Agile methods, managing timelines, budgets, and team resources.
- Drive Data Quality: Build and enforce data quality rules, profiling standards, and monitoring checks to ensure business data is accurate and reliable.
- Fix Data Issues: Set up processes to track, investigate, and fix data errors, missing information, or pipeline failures quickly.
- Align Teams: Act as the bridge between technical teams (Data Engineers, Architects) and business leadership to explain project status and data risks clearly.
- Set Standards & SLAs: Define clear Data Quality rules (SLA/KPIs) for incoming and outgoing data across all business systems.
- Manage Risks & Dependencies: Identify project risks early, remove roadblocks, and keep executive stakeholders updated.
Required Tech Skills & Experience:
- Project Tools: Agile, Scrum, Jira, Confluence, MS Project
- Data Quality Knowledge: Data profiling, root-cause analysis, data lineage, and automated testing rules
- DQ & Governance Tools: Informatica DQ, Great Expectations, Monte Carlo, Collibra, or similar tools
- Technical Basics: Solid understanding of SQL, ETL pipelines, Data Warehouses, and Cloud Platforms (AWS/Azure/Snowflake)
- Certifications (Plus): PMP, CSM (Scrum Master), or CDMP (Certified Data Management Professional)