TERREPOWER is looking to optimize inventory management and global operations by leveraging data-driven initiatives. The Senior Data Analyst will be responsible for enhancing critical databases, developing actionable KPIs, and applying advanced analytics to identify trends and risks, ultimately converting findings into practical changes to improve operational excellence and business outcomes.
Requirements
- strong SQL (joins, CTEs, window functions, performance tuning)
- Power BI (data modeling, DAX, dataflows)
- Experience pulling from ERP/WMS/TMS (Oracle or similar)
- building supply-chain KPIs (inventory accuracy, turns, DOH, OTIF, cost-to-serve)
- Proven track record automating pipelines and maintaining data quality (validation rules, exceptions, monitoring)
- Python/R for deeper analysis
- basics of forecasting/time-series
Responsibilities
- SQL data modeling & ETL: Write performant SQL to extract, clean, join, and automate datasets from ERP/WMS/TMS; create reusable views, stored procedures, and QA checks.
- Semantic models in BI: Build star/snowflake models and dataflows for Power BI; define relationships, measures (DAX), and row-level security to ensure single-source-of-truth reporting.
- Dashboarding & self-service: Develop executive and operator dashboards (inventory accuracy, turns, DOH, fill rate/OTIF, pick accuracy, dock-to-stock, forecast bias); enable drill-through/alerting.
- Performance analytics: Lead root-cause and variance analyses (cycle counts, shrink, service failures, cost drivers); quantify impact and recommend fixes.
- KPI governance: Define metric logic and data lineage; publish documentation and run cadence reviews with Ops/Logistics/Finance.
- Automation & reliability: Schedule refreshes, monitor failures, and implement data quality rules/outlier handling to keep reports accurate and on time.
- Advanced analysis: Apply time-series and regression techniques for demand, inventory, and service forecasting; scenario test “what-if” changes in policy or parameters.
Other
- 6+ years in analytics
- cross-functionally
- convert findings into practical changes
- Translate technical findings for non-technical audiences
- create quick ad-hoc SQL/BI views for DC managers and planners
