Analytics Engineer

Bachelor’s degree in a quantitative field (ex. Data Science, Biomedical Informatics, Computer Science, Biostatistics)

3+ years of experience in analytics or data engineering roles where you are responsible for hands-on cleaning and structuring clinical and electronic health record data

Strong dbt and SQL proficiency: writing reusable Jinja macros, implementing custom tests, and comfortable with multi-environment deployments (dev/staging/prod)

1+ years of experience with extracting, curating, and analyzing data created within the HIT and healthcare delivery ecosystem (e.g., EMR, claims, registry); this may include knowledge of the roles of data exchange and content standards (e.g., FHIR, CDA, CQL) and clinical terminology standards (e.g., ICD, CPT, LOINC, SNOMED-CT, NDC, RxNorm)

Comfort working in a cloud environment (ideally Snowflake and/or AWS).

Proficiency with Git and version control workflows

Is an advocate for bringing software engineering best practices (modularity, unit testing, concise and well-documented code) to a data science team.

Comfortable with ambiguity and creative problem-solving in a fast-paced, rapidly growing startup environment.

Excellent communication skills to advocate for the value of robust analytics engineering solutions and translate customer needs into data solutions.

Passion for improving healthcare and building infrastructure that makes research and clinical AI safer, faster, and more reliable.

Practical experience integrating LLM tools (e.g., Snowflake Cortex, Amazon Bedrock, Azure OpenAI Service) and frameworks (RAG, agent workflows) into data pipelines and product

Proficiency in Python for data cleaning and model feature engineering.

Experience working with AI/ML modeling teams and a conceptual grasp of cloud model deployments and evaluation.

Familiarity with the data aspects of electronic medical records, ex. Epic, Cerner, Allscripts

Any medical ontology experience

Any experience working with DICOM or other imaging modalities

Experience with OMOP common data model

Comfortable with agile tools such as Jira, Linear.

Familiarity using dbt cloud

Our work is fast paced and iterative. We are growing, and we want to support our team members to grow in their skills as well. We are building a team that approaches problems with a diversity of perspectives, values experimentation, and refining our approach based on that experimentation. We work with the full spectrum of healthcare data from tabular data, videos, images, waveforms, etc. If a health system collects it, we might work with it!

If this looks like a partial fit, please reach out, we would love to share more about the work we do for you to understand if it would be a good fit for you.

There is occasional travel for in-person company working days on roughly a quarterly basis.