Funga

Harnessing forest fungal networks to address the biodiversity and climate crises.

Data Infrastructure Engineer

Infrastructure EngineerInfrastructure EngineerFull TimeRemoteTeam 11-50Since 2021H1B No SponsorCompany SiteLinkedIn

Location

United States

Posted

32 days ago

Salary

$120K - $150K / year

Bachelor Degree4 yrs expEnglishAWSCloudDockerETLGoogle Cloud PlatformPost GISPostgresPythonSQLSqlite

Job Description

• 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).

Job 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

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