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Backend Engineer

Job in Austin, Travis County, Texas, 78716, USA
Listing for: Harnham
Full Time position
Listed on 2026-02-16
Job specializations:
  • Software Development
    Data Engineer, Software Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below

What You'll Do

  • Own and evolve the metrics platform, including schemas, storage layouts optimized for high-volume writes and fast analytical reads, and clear versioning strategies
  • Build and maintain a framework for writing and running metrics, including interfaces, examples, local execution, and CI compatibility checks
  • Design and implement testing systems for metrics and pipelines, including unit, contract, and regression tests using synthetic and sampled data
  • Operate compute and storage systems in production, with responsibility for monitoring, debugging, stability, and cost awareness
  • Partner with metric authors and stakeholders across development, analytics, and QA to plan changes and roll them out safely
What Youll Need
  • Strong experience using Python in production
    , including asynchronous programming (e.g., asyncio, aiohttp, FastAPI)
  • Advanced SQL skills, including complex joins, window functions, CTEs, and query optimization through execution plan analysis
  • Solid understanding of data structures and algorithms
    , with the ability to make informed performance trade-offs
  • Experience with databases
    , especially PostgreSQL (required); experience with Click House is a strong plus
  • Understanding of OLTP vs. OLAP trade-offs and how schema and storage decisions affect performance
  • Experience with workflow orchestration tools such as Airflow (used today), Prefect, Argo, or Dagster
  • Familiarity with data libraries and validation frameworks (Num Py, pandas, Pydantic, or equivalents)
  • Experience building web services (FastAPI, Flask, Django, or similar)
  • Comfort working with containers and orchestration tools like Docker and Kubernetes
  • Experience working with large-scale datasets and data-intensive systems
Nice to Have
  • Ability to read and make small changes in C++ code
  • Experience building ML-adjacent metrics or evaluation infrastructure
  • Familiarity with Parquet and object storage layout/partitioning strategies
  • Experience with Kafka or task queues
  • Exposure to basic observability practices (logging, metrics, tracing)
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