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Turquoise HealthTurquoise HealthSan Diego, CA

Data Science Engineer, Analytics

Build data pipelines, models, dashboards, and analyses to support product and business decision-making. Requires 2+ years of Python/SQL experience with data modeling, ETL tools, and AWS.

145k – 160k/yr
Remote2+ YOEData Engineering

About the role

Responsibilities

  • Partner cross-functionally with Product, Engineering, and business stakeholders to define metrics, measure outcomes, and evaluate impact
  • Build and maintain data pipelines, data models, dashboards, and analytical infrastructure that support product, operational, and strategic decision-making
  • Conduct analyses to understand product adoption, customer engagement, business performance, and operational efficiency
  • Contribute to the development of analytics best practices, shared datasets, and company-wide metrics
  • Seek and act on feedback from internal stakeholders; iterate quickly with an eye toward value

Requirements

  • Bachelor's degree or equivalent experience
  • 2+ years developing data models, pipelines, and end-to-end analytical solutions in Python and SQL
  • Comfortable with OOP and functional patterns, code organization beyond scripts, and debugging workflows
  • Experience with dataframe libraries (pandas, polars)
  • Experience with ETL/ELT workflows and orchestration (Airflow, dbt)
  • Comfort with cloud services (AWS S3, EC2, RDS)
  • Ability to design data systems with scalability, performance, and cost efficiency in mind, particularly for compute- and data-intensive workloads
  • Entrepreneurial mindset: prioritize tasks with an eye for evolving business needs
  • Comfortable working remotely in a collaborative, technical team

Nice-to-Haves

  • Experience with b2b healthcare product analytics
  • Experience applying quantitative methods (regression, causal inference) to product or business questions
  • Thoughtful use of AI coding agents and LLMs in development workflows

Skills

PythonSQLpandasPolarsAirflowdbtAws S3Aws Ec2Aws RdsETLELT

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