Design, build, and maintain production ETL pipelines and data models on Databricks, supporting daily and hourly business-critical workflows.
Own the analytics data layer from raw ingestion through dimensional modeling to BI tool-ready outputs while ensuring data quality, freshness, and reliability.
Build and maintain integrations with third-party platforms, including mobile attribution, CRM, payment processors, and ad platforms.
Develop and maintain regulatory compliance data systems.
Partner directly with Finance, Marketing, Product, and CustOps stakeholders to translate business questions into data solutions from ad-hoc analyses to automated reporting.
Build financial reconciliation pipelines with 99%+ accuracy to support revenue tracking, cost allocation, and executive reporting.
Monitor production job health, triage failures, and maintain SLAs across 20+ scheduled pipelines.
Drive data architecture decisions, establish conventions, and document systems for long-term maintainability.

5+ years of experience in data engineering, analytics engineering, or a hybrid data role, delivering production-grade pipelines and business-facing analytics.
Advanced SQL skills, including window functions, MERGE patterns, incremental loads, and complex multi-table joins.
Strong Python proficiency for ETL workflows, API integrations, and data transformations.
Experience owning a full data stack as the primary data professional in a fast-moving environment.
Proven ability to work cross-functionally, translating requests from non-technical stakeholders into reliable data products.
Demonstrated experience handling PII, financial data, and compliance-sensitive workflows with a focus on security and accuracy.
Exceptional communication skills, with the ability to explain data findings clearly to stakeholders.

Senior Analytics Engineer

Key skills