Senior Data Engineer

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, though growth opportunities exist over time

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