Business Intelligence Engineer

- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with scripting language (e.g., Python, Java, or R)
- Experience building and maintaining basic data artifacts (e.g., ETL, data models, queries)
- Experience gathering business requirements, using industry standard business intelligence tool(s) to extract data, formulate metrics and build reports
- Knowledge of BI analytics, reporting or visualization tools like Tableau, AWS QuickSight, Cognos or other third-party tools
- Knowledge of data modeling and data pipeline design
- Master's degree, or Advanced technical degree
- Experience with statistical analysis, co-relation analysis

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We are seeking a data-driven Business Intelligence Engineer (BIE) to join the IN Value Commerce team. In this role, you will be responsible for building scalable analytics solutions, creating actionable insights, and developing automated reporting frameworks to drive growth in the <500 segment.
You will work closely with business stakeholders, product managers, and SDE's to:
1) Define and track key metrics related to selection health, selection gaps, catalog coverage, and customer demand signals in the <₹500 price band.
2) Build and maintain data pipelines and ETL processes to support reporting and analytics needs for the Value Commerce program.
3) Develop dashboards and self-service BI tools (QuickSight, Tableau, or equivalent) to enable stakeholders to monitor selection KPIs, glide paths, and WBR/MBR metrics.
4) Conduct deep-dive analyses to identify selection gaps, competitive benchmarking insights, and growth opportunities within the <500 space.
5) Automate reporting workflows to reduce manual effort, improve data freshness, and scale analytics.
Improve data quality and governance by defining data contracts, validation checks, and documentation standards for the team's data assets.

About the team
The IN Value Commerce team manages A.in's sub ₹500 price segment units growth and customer growth. The team works cross-functionally with Category, Seller, Marketing, and Product teams to unlock selection, improve pricing, improve discoverability to deliver sub ₹500 input and output goals.