Engineering Manager, Enterprise Data Warehouse & Analytics

What You'll Do

• Own the data model. Design and evolve the conformed dimensional model and the standards the team builds against. Review every new model for grain and conformance.
• Build and run the pipelines. Design ETL/ELT from source systems through bronze -> silver -> gold on Databricks, with incremental loads, data contracts, and Airflow orchestration.
• Own the semantic layer. Build governed metrics in Unity Catalog metric views and Power BI semantic models, so every dashboard, report, and LLM query uses the same definitions.
• Deliver reliable operational metrics. Turn KPI definitions from Product and Operations into certified models and metrics, reconciled to source and delivered through dashboards and self-service.
• Assure the numbers. Own reconciliation, data tests, freshness and anomaly monitoring, SLOs, and CI/CD for data.
• Modernize orchestration. Lead the move of dbt orchestration from dbt Cloud to Airflow without gaps in data freshness.
• Partner with Product. Work with your Product counterpart and business stakeholders to shape requirements. You own the technical plan: architecture, sequencing, estimates, and trade-offs.
• Lead the team. Manage, coach, and hire analytics engineers and BI analysts. Run sprint execution and set the bar for code review, testing, documentation, and AI-assisted development.

What You Bring

• 10+ years in data warehousing, data engineering, or analytics engineering, including 3+ years as a hands-on engineering manager.
• Expert in dimensional modeling: grain, fact types, conformed dimensions, slowly changing dimensions, bridge tables, and the bus matrix. Has built an enterprise warehouse across multiple source systems and owned it in production
• Expert SQL and dbt: complex SQL and performance tuning; dbt models, tests, macros, packages, and CI
• Databricks in production: Spark SQL, Delta Lake, Unity Catalog, and medallion architecture. Deep Snowflake or BigQuery experience will be considered
• Semantic layer: has built governed metrics (Databricks metric views, dbt Semantic Layer/MetricFlow, Cube, or Power BI semantic models) and the BI on top. Power BI/DAX preferred
• ETL/ELT and orchestration: has designed and run production pipelines with incremental loads, snapshots or CDC, and Airflow (or a similar orchestrator). Python for pipeline work
• Data quality: testing, reconciliation, observability, and CI/CD for data
• Cross-functional partner: works well with a Product counterpart and business stakeholders. Turns requirements into technical designs and explains trade-offs in plain language

Nice to have

• Healthcare claims or payment integrity data
• Building operational KPIs with business operators
• LLM-based self-service analytics (e.g., Databricks Genie)
• Experience leading teams across time zones

What We Offer

• Work from anywhere in the US! Machinify is digital-first.
• Full Medical/Dental/Vision for employees & their families
• Flexible and trusting environment where you'll feel empowered to do your best work
• Unlimited FTO
• Competitive salary, equity, 401(k) including employer match

Base Salary: $220,000-$260,000

The salary for this position is based on an array of factors unique to each candidate: Such as years and depth of experience, set skills, certifications, etc. We are hiring for different levels, and our Recruiting team will let you know if you qualify for a different role/range. Salary is one component of the total compensation package, which includes meaningful equity, excellent healthcare, flexible time off, and other benefits and perks.