M- Work from
- United States
- Contract
- Full-time
- Salary
- $220K – $260K / year
- Posted
- 11 November 2026
- Apply by
- 10 January 2027
Next, you'll extend the warehouse to new business domains with a repeatable, template-driven approach.
The foundation is already in production: a Databricks lakehouse with 600+ dbt models, 1,800+ automated tests, Power BI semantic models, and LLM self-service on governed metrics. Your first priority isoperational measurement: building the trusted metrics our Operations leaders run their business on.
This is a hands-on Engineering Manager role on a flat team. You'll manage engineers and analysts directly and spend about half your time building: designing the dimensional model, writing and reviewing code, and setting the engineering standards. You'll partner closely with a Product counterpart who owns priorities and stakeholder intake, so you can focus on architecture, delivery, and the team.
Responsibilities
- 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.
Requirements
- 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
Benefits
- 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
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.
About Machinify
Machinify is a leading healthcare intelligence company with expertise across the payment continuum, delivering unmatched value, transparency, and efficiency to health plan clients across the country. Deployed by over 85 health plans, including many of the top 20, and representing more than 270 million lives, Machinify brings together a fully configurable and content-rich, AI-powered platform along with best-in-class expertise. We’re constantly reimagining what’s possible in our industry, creating disruptively simple, powerfully clear ways to maximize financial outcomes and drive down healthcare costs.
Machinify brings together several payment integrity and recovery businesses for health plans. Each one produces numbers that executives, operations leaders, and clients act on. Your job is to make sure there is one warehouse, one conformed model, and one definition of every number.
Equal Employment Opportunity at Machinify
We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal opportunity workplace. Machinify is an employment at will employer. We participate in E-Verify as required by applicable law. In accordance with applicable state laws, we do not inquire about salary history during the recruitment process. If you require a reasonable accommodation to complete any part of the application or recruitment process, please let our recruiters know. See our Candidate Privacy Notice at:
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