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Machinify

AI-driven healthcare operations optimization platform

Senior Data Engineer - Analytics

Data Engineering +1Confirmed live in the last 24 hours
Full-timeRemote in USA

About the Job

Requirements

  • At least 6 years of experience across analytics engineering, business intelligence engineering, data engineering, or business analysis, including production ownership of models and metrics.
  • Expert SQL skills and strong dimensional modeling instincts.
  • Production experience with dbt, including models, tests, macros, exposures, documentation, and continuous integration.
  • Hands-on experience with a cloud lakehouse or warehouse; Databricks and Spark SQL are preferred, while Snowflake, BigQuery, or Redshift experience is transferable.
  • Experience owning a business intelligence semantic layer and reports built on it; Power BI and DAX are preferred, with Looker/LookML, Tableau, MetricFlow, or Cube as substitutes.
  • Ability to run requirements conversations with non-technical owners, turn vague complaints into testable definitions, explain data problems as business risks, and address incorrect metrics effectively.
  • A reconciliation-focused approach to investigating discrepancies between numbers.
  • Experience using Git and pull-request workflows.
  • Ability to use Python for appropriate tasks such as API calls, file parsing, statistics, or report generation, and to use SQL where appropriate.
  • Comfort working with high autonomy in a fast, asynchronous, Slack-first environment.
  • Strong writing skills for documents, definitions, and charts intended to be understood without live explanation.

Responsibilities

  • Run discovery with business stakeholders, identify the underlying need behind requests, and turn it into buildable acceptance criteria.
  • Model noisy healthcare operational data into certified dimensional models across the Databricks bronze-to-silver-to-gold architecture using dbt and SQL.
  • Own metric definitions by documenting one governed definition for each measure in a semantic layer that non-engineers can understand.
  • Build and own Power BI semantic models, dashboards, and paginated reports, including refresh health and semantic-model currency; select appropriate visualizations and explain design choices.
  • Own model observability, including freshness and latency detection, statistical anomaly detection, value-drift monitoring, data tests, regression guards, and continuous-integration checks.
  • Own orchestration for built solutions, including dbt Cloud job design, Airflow DAGs, scheduling, dependency ordering, and dependable incremental runs.
  • Create design documents, model documentation, a continuous-integration-enforced knowledge base, and business-readable handoff packets.
  • Automate recurring work through repeatable, testable, AI-assisted workflows, directing large language models and supervising their outputs.

Desired Qualifications

  • Healthcare data experience, including claims (837/835/UB04), DRG and coding review, payment integrity, provider contracts, or revenue cycle.
  • Experience with data contracts, schema enforcement, ODCS-style governance, or quality gating in continuous integration.
  • Experience with Databricks Unity Catalog, lineage, and cost or DBU accountability.
  • Experience with paginated reporting, SharePoint/Excel delivery, or other business reporting surfaces with specific format requirements.
  • Experience working alongside AI coding agents and reviewing their outputs against a written contract.
  • Databricks and Spark SQL experience.
  • Power BI and DAX experience; Looker/LookML, Tableau, MetricFlow, or Cube are credible alternatives.

About the Company

Machinify

AI-driven healthcare operations optimization platform

Machinify uses artificial intelligence to optimize decision-making in healthcare. It provides AI-driven applications that improve operational efficiency for health plans, payers, and providers, acting as a central nervous system to manage data-driven decisions. Its products streamline processes like claims processing and utilization management by deploying a growing portfolio of applications on the Machinify platform, designed for fast implementation and immediate ROI. Differences from competitors include an AI-first platform tailored to healthcare administration, a rapid deployment model, and a customer-focused approach that aims to deliver tangible results quickly. The company’s goal is to transform healthcare administration by reclaiming control over healthcare expenditures and improving efficiency and patient outcomes through data-driven decisions.

Company size
1,001-5,000
Company stage
Series A
Total funding
$15.6M
Headquarters
Palo Alto, CA
Founded
2016

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