Data Analytics Engineer

Values

Primary Responsibilities

• Requirements Discovery & Scoping — Partner with business stakeholders to uncover true requirements — even when the business itself isn’t sure what it needs — and translate them into clear, actionable requirements and tasks for Data Engineering and BI teams.
• Reverse-engineering existing solutions — Analyze and reverse-engineer current business processes and existing IT/reporting solutions (legacy reports, spreadsheets, ERP systems) to understand current-state logic before scoping the ODP solution.
• Data Analysis & Manipulation — Perform hands-on data analysis and manipulation to validate assumptions, generate correct results, and determine how data should be modeled into or out of ODP.
• Solution Scoping & Handoff — Define the scope and shape of solutions to be built in ODP, and hand off clear, well-defined requirements to Data Engineers and BI/report developers.
• Relationship-driven Problem Solving — Build and maintain strong relationships across the business, IT, and the EDM team — the primary source of context and answers when requirements are unclear or undocumented.
• Proactive Issue Detection — Proactively identify data and solution issues before the business surfaces them, through ongoing data validation and review.
• Troubleshooting & Resolution — Troubleshoot and resolve data issues, partnering with Data Engineering when root causes sit upstream in pipelines or source systems.
• Solution Adoption — Partner with the business throughout build and rollout to ensure the delivered solution meets or exceeds requirements and is fully adopted.
• Cross-functional Collaboration — Interact heavily with technical and non-technical business stakeholders, power users, other IT teams, and the EDM team throughout the analysis-to-delivery lifecycle.