Data Engineer

Who we are: At Arkana Laboratories, everyone has an important role to fill. Come join us and be a part of a team dedicated to making life better for those who need it most. This place is packed with super‑smart people who do their best work together. We work hard every day to advance our understanding of disease and provide world‑class care to our patients in hopes of leaving our corner of the world a little better than we found it.

While we are committed to improving the lives of thousands of patients, we never lose sight of the fact that they are the reason we get to create change in our field. Built on generosity, teamwork, and the freedom to try new things, we take great pride in our work. Great ideas come from everywhere in this company and we celebrate each success and failure for the opportunity it gives us to keep reaching.

For more than twenty years after our founder, Dr. Patrick Walker, wrote his goals on the back of a napkin, our people, culture, and values have remained strong.

Arkana Laboratories is building a next‑generation Laboratory Information System: a modular, cloud‑native platform that will power every facet of our renal pathology workflow. The Data Engineer sits at the intersection of application development and analytics and owns the data layer that both groups depend on. Day to day, that means designing and maintaining schemas, building reliable ETL/ELT pipelines, partnering with developers on data contracts, and ensuring analysts have clean, well‑documented data to work from.

This role works inside a small, high‑ownership data team and collaborates directly with backend engineers, product managers, and analysts. The work spans both halves of the operational/analytical boundary, and the engineer is expected to be fluent on both sides.

• Design and maintain Postgre
  
  SQL schemas (multi‑schema architecture) for LIS application modules
• Author and review Prisma migrations
• Develop data contracts defining access patterns and interface expectations between application modules and the data layer
• Participate in design sprints alongside backend developers and bring data layer constraints into architecture decisions early
• Generate and maintain synthetic test datasets for safe development and QA without production PHI exposure

• Design, build, and operate ETL/ELT pipelines ingesting data from legacy systems and external sources
• Own pipeline reliability end‑to‑end: monitoring, alerting, retry logic, and runbooks the rest of the team can use
• Help close the open ETL tooling decision (in‑app code vs. Azure Data Factory vs. hybrid) and implement the chosen approach
• Build FHIR transformation pipelines that produce clean, clinically relevant output for application consumption

• Maintain and evolve the data warehouse to support dashboards, operational reporting, and ad hoc queries
• Partner with analysts to translate reporting requirements into performant, well‑documented data models
• Evaluate Snowflake or similar platforms as analytical reporting demands grow

• Own the team's data dictionary and documentation standards
• Implement audit‑trail and history‑table patterns satisfying both HIPAA compliance and operational reporting needs
• Enforce data access controls and column‑level security appropriate for a HIPAA and HITRUST environment

• Serve as the data team's representative in design sprints and help enforce intake and triage processes for development team requests
• Mentor analysts growing into data engineering responsibilities
• Produce documentation that makes your work maintainable by others

• Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related technical field. Equivalent demonstrated experience considered.

• 3‑6+ years of hands‑on data engineering experience in a production environment, with strong SQL skills including complex queries, query optimization, window functions, and indexing strategies.

• Experience designing relational schemas in Postgre
  
  SQL…