Key skills
AirflowAWSDockerMySQLNeo4jPostgresPythonRAIMLLLMData EngineeringAnalyticsFastAPIECSLambdaS3Version ControlCI/CD
About this role
Role Overview
- Architect, implement, and maintain data ingestion and transformation pipelines using modern workflow orchestration tools (e.g. Dagster).
- Identify, catalog, and integrate internal and external data sources used across research efforts.
- Operationalize bioinformatics pipelines that support large-scale batch processing, incremental updates, and backfills within AWS.
- Normalize and structure heterogeneous data into consistent, reusable representations that support downstream analysis, modeling, and querying.
- Populate and maintain patient-centric data models in shared storage systems (e.g., graph and relational databases).
- Collaborate with backend and AI engineers to design data-access patterns that support analytics applications and AI-driven interactions.
- Contribute to backend services and APIs that expose integrated data to internal tools and applications.
- Participate in the evolution of AI-enabled analysis workflows, including tooling that supports LLM
- or agent-based interactions with data.
- Contribute to system-level design decisions around data flow, service boundaries, reliability, and scalability.
- Write clean, tested, and well-documented Python code that meets production software engineering standards.
- Debug and resolve complex data quality, pipeline, backend, and infrastructure issues in a distributed environment.
Requirements
- BS in Computer Science, Bioinformatics, Computational Biology, or a related field, MS preferred.
- 4+ years of experience in production data engineering or software engineering.
- Independently drive technical solutions from high-level goals, exercising judgment in system design, implementation, and tradeoff evaluation.
- Strong proficiency in Python, with experience writing maintainable, production-quality code across data and backend contexts.
- Extensive experience with software engineering fundamentals, design patterns, version control, CI/CD, Docker, and automated testing.
- Experience designing and operating workflow orchestration systems (Dagster preferred; Airflow, Prefect, or similar acceptable).
- Experience building or contributing to backend services (e.g., FastAPI or similar frameworks).
- Hands-on experience with AWS services commonly used in data and backend systems (e.g., S3, ECS, Batch, Lambda).
- Experience deploying and operating large-scale data or bioinformatics pipelines in AWS, including managing throughput, cost, and operational reliability.
- Experience with relational databases (Postgres, MySQL) and/or graph databases (Neo4j), including schema and query design.
- Experience contributing to system-level architecture, including data modeling, service boundaries, and operational robustness.
- Ability to work effectively with scientists, bioinformaticians, and ML practitioners in an R&D environment.
Tech Stack
- Airflow
- AWS
- Docker
- MySQL
- Neo4j
- Postgres
- Python
Benefits
- Comprehensive medical, dental, vision, life and disability plans for eligible employees and their dependents.
- Free testing for Natera employees and their immediate families in addition to fertility care benefits.
- Pregnancy and baby bonding leave.
- 401k benefits.
- Commuter benefits.
- Generous employee referral program!