Data Engineer
Build and maintain scalable data models, pipelines, and Core Data tables to transform raw data into actionable insights. Collaborate with data scientists and business teams using SQL, DBT, Snowflake, Airflow, and Python.
Founding Analytics Engineer
Founding Analytics Engineer builds analytics infrastructure from scratch, designs data models and metrics frameworks for healthcare financial data, and creates self-service dashboards. Requires 5+ years experience with SQL, dbt, Python, and cloud data warehouses; NYC-based hybrid role.
120k – 235kNew York, NYData EngineeringHybrid5+ YOE
About the role
Responsibilities
- Build the analytics infrastructure from scratch - design and implement the entire analytics stack, including the data warehouse architecture, transformation layer, semantic layer, and visualization tools.
- Establish foundational data models - create robust, scalable data models that transform raw healthcare financial data into clear, actionable metrics and insights.
- Design the metrics framework - work with leadership to define key business metrics, establish metrics definitions, and build the infrastructure to track them reliably.
- Create self-service analytics capabilities - build intuitive dashboards and analytics tools that enable both internal teams and customers to understand revenue cycle performance, identify uncollected revenue, and track financial health.
- Drive the analytics roadmap - partner closely with product, engineering, and customer success to prioritize analytics initiatives, define requirements, and ensure we're building the right solutions.
- Build data transformation pipelines - implement modern ELT/ETL patterns using tools like dbt to ensure data quality, reliability, and performance at scale.
- Establish best practices and standards - define data governance policies, documentation standards, testing frameworks, and code review processes.
- Define business logic - collaborate on complex revenue recognition rules, financial calculations, and healthcare billing logic.
Requirements
- 5+ years of experience in analytics engineering, data analytics, or business intelligence, with a focus on building data models and metrics frameworks.
- Proficiency in SQL and data modeling best practices.
- Modern analytics tools such as dbt, Looker, Tableau, or similar.
- Python for data analysis and automation.
- Data warehousing concepts and cloud data platforms (Snowflake, BigQuery, Redshift, etc.).
- Version control and CI/CD workflows such as GitHub Actions.
Nice-to-Haves
- Experience working with healthcare data or financial analytics.
Compensation
- Base pay range: $120,000–$235,000 per year.
- Competitive compensation packages and strong equity.
Skills
SQLdbtLookerTableauPythonSnowflakeBigQueryRedshiftGitHub ActionsData Modeling
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