Own the Stack: Architect and maintain our central storage (PostgreSQL/PostGIS, SQLite) and cloud environment (AWS/GCP), leveraging ECS, Lambda, and S3.
Modern DevOps: Standardize environments using Docker, CI/CD pipelines, and Infrastructure as Code to automate the testing and deployment of data services.
Scale for Performance: Optimize data models and database performance management for extensibility as our genomic and geospatial inputs scale.
Build Lean Ingest: Design and automate scalable ELT/ETL pipelines for genomic, geospatial, and tabular data from sources like Survey123, ArcGIS, and Asana.
QA/QC at Scale: Build automated validation pipelines to ensure data integrity and version control from the moment it hits our system.
Internal Enablement: Support scientists and operational teams by designing the data models that power internal modeling workflows, dashboards, and reporting.
System Connectivity: Develop lightweight APIs and connectors to sync data between our core infrastructure and downstream applications (e.g. Asana, ArcGIS, and internal dashboards).

Requirements

4+ years of experience in Data or Backend Engineering, with a track record of building production data systems from the ground up.
Database expertise: Deep SQL proficiency. You understand indexing, partitioning, and optimizing Postgres for high performance.
Cloud Infrastructure: Significant experience building, managing, and optimizing data services within AWS or GCP (e.g. ECS, Lambda, RDS) with a focus on cost-effective, maintainable architecture.
Modern DevOps & Python: Proficiency in production-grade Python and modern DevOps practices, including containerization (Docker), CI/CD pipelines, and infrastructure monitoring.
Data fluency: Experience handling large-scale Parquet, Avro, binary, or similar data types. Familiarity with geospatial data types and tools (PostGIS, GDAL) is a plus.
Product mindset: You treat internal teams as your customers. You are driven to build solutions that serve and accelerate internal teams' work.
Pragmatic: You prefer simple, mature, composable tools over heavy, managed platforms, and you have a bias for creating value now versus perfection later.

Benefits

Comprehensive Benefits: Participate in healthcare benefits and employee equity programs.
Flexible time off policy
Wellness reimbursement program

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PostgreSQLPostGISSQLiteAWSGCPDockerCI/CDPythonELTETL

Soft Skills

product mindsetpragmaticdata fluency