Senior Data Engineer
Builds and maintains end-to-end data pipelines from raw ingestion to analysis, using Python, SQL, and AI tools to create actionable insights for healthcare clients and internal teams. Requires 4+ years experience handling complex data systems with focus on quality and observability.
About the job
Responsibilities
- Drive Prompt’s mission to improve healthcare through high-quality, actionable data that informs client and internal decision-making
- Own the design, development, and iteration of complex data systems — from raw data ingestion through transformation, modeling, and downstream analysis
- Perform exploratory analysis and hypothesis-driven investigations to surface insights and guide both client-facing and internal decision-making
- Leverage modern AI and LLM-powered tools (e.g., code assistants, agents, automation frameworks) to accelerate data transformation, analysis, and iteration — while maintaining high standards for reliability, security, and maintainability
- Develop and evolve well-modeled datasets, complex transformations, and metrics
- Design and implement data quality checks, monitoring, and observability to ensure correctness, freshness, and trust in data products
- Partner with stakeholders across the company to understand client and internal workflows, define success criteria, and deliver data products to drive improvement
Qualifications
- 4+ years of experience building data systems, including data pipelines, transformations, and analytical datasets
- Strong experience designing, building, and operating end-to-end data workflows—from raw data ingestion through transformation, modeling, and downstream analysis
- Proven ability to work with complex, messy, and evolving data sources and turn them into reliable, well-modeled datasets
- Experience performing exploratory and hypothesis-driven analysis to inform product, operational, or client-facing decisions
- Strong judgment around data quality, correctness, observability, and maintainability in production data systems
- Strong proficiency in Python and SQL for data transformation, analysis, and pipeline development
- Experience leveraging modern AI and LLM-powered tools (e.g., code assistants, agents, automation frameworks) to accelerate data engineering and analysis workflows
- Strong problem-solving mindset and ability to operate effectively in ambiguous, fast-paced environments
- Interest in a hands-on, high code-contribution role; this is not an engineering management position
Nice-to-Haves
- Experience with complex healthcare datasets – including patient care, operations, and billing data
- Hands-on experience with analytics engineering tools such as dbt for data transformations and Metabase for building analytics dashboards (or other data transformation and dashboarding tools)
- Experience working in AWS (e.g., S3, Athena, RDS, Redshift, DMS, Glue, ECS, Lambda, or similar services)
- Experience working with relational databases and warehouses (e.g., PostgreSQL, Athena, Redshift, Snowflake, BigQuery)
- Experience building internal or client-facing analytics products used by multiple teams or customers
Skills
Python, SQL, dbt, Metabase, AWS, S3, Athena, Redshift, Postgres, Snowflake
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