Data Engineer for BI Dashboards

We are seeking a data engineer to manage the data layer for our BI analytics dashboards in an e-commerce setting. The role involves ensuring data accuracy and integrity, optimizing data processes, and collaborating with cross-functional teams to enhance our analytics capabilities. What you'll do - Design and maintain BigQuery datasets, tables, and views for BI dashboards - Build clean, well-structured transformation logic (SQL / data models) from raw source data into analytics-ready marts - Pull data from external sources into BigQuery via scripting and API calls (REST APIs, pagination, auth, scheduling) - Translate finance & operations metrics into correct, reliable data models(revenue, margin, cash flow, open items, cost allocation, etc.) - Ensure data quality, consistency, and sensible naming conventions across datasets - Document your models, logic, and assumptions so the team can build on them - Collaborate on metric definitions and flag inconsistencies proactively. Required skills - Strong hands-on experience with Google BigQuery (SQL, partitioning, scheduled queries, query optimization, cost-aware design) - Scripting & API integration — comfortable writing scripts (e.g. Python) to call external APIs, handle auth and pagination, and load the results into - BigQuery - Solid data engineering fundamentals: data modeling, ELT/ETL concepts, incremental loads, source-to-mart layering - Understanding of finance processes and terminology — you should know what metrics like revenue recognition, gross margin, contribution margin, COGS, accruals, and open items actually mean, not just how to SUM a column - Clean, structured working style with strong attention to data correctness - Ability to write clear documentation (data dictionaries, model descriptions, assumptions)