Senior Data Engineer, Healthcare Data

The posting, as Headwater Science wrote it

About Headwater Science

Headwater Science (formerly NoviSci) is a data science and methods company specializing in principled, reproducible evidence generation for complex clinical and regulatory challenges. With deep expertise in comparative effectiveness, causal inference, healthcare utilization and expenditure research, and regulatory-grade analytical software, Headwater Science provides the methodological foundation that delivers reproducible analytic pipelines, novel epidemiologic and statistical methods, and regulatory-grade software validated to hold up under the most demanding scrutiny. The company works with life sciences organizations as a long-term scientific partner. Headwater Science is a Highlander Health company. Learn more at headwaterscience.com.

The Role

We are seeking a talented Senior Data Engineer to design, build, and maintain the data pipelines that power our real-world evidence research.

Our studies depend on turning large, messy, vendored healthcare data into analytic-ready datasets that epidemiologists and statisticians can trust. You’ll help us construct these datasets alongside our statistical programming team, and you’ll also help shape the processes, systems, and infrastructure that produce regulatory-grade data. That includes collaborating with our software development team to define the tools that need to exist, the workflows those tools support, and the requirements they have to meet. It also includes serving as the technical point of contact for our administrative claims and EHR data vendors and becoming our in-house expert on each source’s structure, conventions, and limitations.

This is a hands-on role. Much of your time will be spent inside real studies with tight deadlines, and the standards and tooling you build will grow out of that work rather than in isolation. Today the work runs on R, SQL, and AWS, and while AWS is here to stay, you'll have a voice in how the rest of the stack evolves to meet the needs of our studies. We’re a small team with broad scope, and as our data engineering work expands, there’s room for this role to grow with it.

How We Work

Inside a study, you’ll be one of several people working closely with the epidemiology team to ensure that the analytic-ready dataset faithfully follows the study protocol, and you’ll report back on what you learn about the data along the way. Those datasets are consumed by our statisticians, so you’ll also be in close contact with them around data deliveries: keeping them informed on timelines, documenting what’s in each delivery, and answering questions as the analysis takes shape.

Across studies, you’ll work with the statistical programmers who use the systems and procedures you help shape. You’ll support them day to day as they build datasets on active projects, and you’ll also help refine the procedural requirements they follow: how data are accessed, how pipelines are structured and documented, and what a finished dataset has to satisfy be
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• 5+ years designing, building, and owning production data pipelines, including ingestion of large files, quality validation, reproducibility, and version control.
• Experience processing and transforming large datasets in relational databases or distributed query engines such as Spark, whether through SQL directly or APIs.
• Experience designing software, including writing requirements documents and specifying programming interfaces.
• Proficiency in R, or a willingness to learn it. Our current data processing pipelines are written in R.
• Experience building on AWS.
• A track record of turning ad hoc practices into documented, repeatable processes for a team of programmers or analysts.
• Experience evaluating and selecting data tools and architecture, including the tradeoffs involved in adopting or replacing a technology.

Nice to Have

• Hands-on experience with administrative claims or EHR data, including their coding systems and enrollment logic. Familiarity with common data models such as OMOP is a plus.
• Exposure to modern data engineering technologies such as Snowflake, Spark, AWS Batch, S3, Arrow, Docker, and GitLab CI.
• A working knowledge of pipeline orchestration frameworks such as Airflow, targets, Nextflow, or Snakemake.
• Experience handling protected health information or other regulated data.
• Familiarity with software validation practices under frameworks such as GxP or 21 CFR Part 11.

What We Offer

• Hybrid work — 3 days/week in office to collaborate with the team
• Comprehensive health, dental, and vision for you and your family
• 401(k) with company match
• Generous PTO and company holidays
• Paid parental leave

If you are ready to be part of a team where your work truly matters- where your expertise is valued, your growth is supported, and your contributions help shape the future of healthcare- Headwater Science is the place for you. We’re building something meaningful together, and we’d love for you to be a part of it.