Data Engineer

Headwater Science•Raleigh, NC

42d•Hybrid

About The Position

We are seeking a talented Data Engineer to design, build, and maintain the data pipelines and software infrastructure that power our real-world evidence research. Working primarily in R, Python, and SQL, you'll create clean, scalable solutions that transform healthcare data into research-ready resources - managing collaborative development through Git and GitLab, maintaining CI/CD tooling that keeps code tested and reproducible, and supporting cloud-based infrastructure (AWS preferred). You'll partner closely with operations and product teams on deployment, testing, and troubleshooting, and help drive ongoing improvements to our systems that support Headwater Science’s mission.

Requirements

Bachelor’s degree in computer science, engineering or a related field (or equivalent practical experience).
Background in healthcare, life sciences, or clinical data.
3+ years of software development experience, ideally in data engineering, data platform development, or backend systems.
Experience with cloud platforms (AWS, GCP, or Azure) and working in cloud-native environments.
Strong problem-solving and communication skills.
Ability to work independently and manage tasks with moderate supervision.

Nice To Haves

R package development, SQL, Python, version control and CI/CD tools (e.g., GitLab, GitHub Actions).
Familiarity with software validation practices for regulated or regulatory-grade environments.
Experience working with or developing machine learning pipelines or models.
Exposure to Generative AI or LLM frameworks (e.g., Langchain, LangGraph).
Knowledge of distributed computing concepts or tools (e.g., Spark, Dask).
Knowledge of command-line workflows in UNIX/Linux environments.

Responsibilities

Design and implement data pipelines and software solutions that promote operational efficiency and scalability.
Write clean, maintainable code primarily in R and Python, with a strong emphasis on SQL for data manipulation and transformation.
Manage collaborative development through Git and GitLab, and maintain the CI/CD tooling to ensure tested, validated and reproducible code.
Support and optimize cloud-based data infrastructure (AWS preferred).
Develop and modify databases to support internal applications.
Collaborate with operations and product teams to support deployment, testing, and maintenance.
Help troubleshoot production issues and contribute to ongoing improvement efforts.
Stay up to date on relevant tools, technologies, and best practices.