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Harnham Linkedin · Posted 15d ago

Staff Data Engineer

San Francisco, CA, United States

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Staff Data Engineer

San Francisco, CA

$240K–$300K base + equity


We're partnered with one of the most recognized developer platforms in the world, trusted by engineering teams at OpenAI, Meta, Netflix, and Adobe, who are scaling their data platform and looking to hire a Senior Data Engineer to own the pipelines and foundations at the core of their data ecosystem.


You'll own the full pipeline lifecycle, from ingestion architecture through to analytics-ready data, working closely with Data Platform Engineers and partnering with analysts and data scientists who depend on what you build every day.


What You’ll Do

  • Design and build scalable ingestion pipelines and orchestration frameworks across structured, semi-structured, and event-based sources
  • Own reliability, observability, and performance across the full pipeline lifecycle from raw ingestion to analytics-ready delivery
  • Build and maintain dbt transformation pipelines serving as the single source of truth across Finance, Product, GTM, and Engineering
  • Ensure revenue and billing data meets the accuracy and auditability required for public company reporting, including SOX compliance
  • Apply software engineering principles throughout: CI/CD, testing, observability, version control, and automation
  • Enable self-serve analytics through semantic layer development, strong abstractions, and clear documentation
  • Champion data quality and governance across classification, ownership, access policies, and data lifecycle management


What We’re Looking For

  • 8+ years in data engineering or a hybrid data/analytics engineering role, with a track record of owning pipelines end-to-end in high-growth or enterprise environments
  • Advanced SQL and dbt (Core or Cloud), Snowflake or comparable cloud data warehouse, Python, and Airflow
  • Deep experience with Kafka and streaming data systems, with strong working knowledge of ClickHouse, Iceberg, or similar technologies
  • Experience with ingestion tools such as Fivetran, Airbyte, or Polytomic
  • Cloud-native architecture expertise across AWS, GCP, or Azure
  • Experience designing and scaling data systems to support petabyte-level workloads
  • Track record of building data infrastructure that meets compliance and governance requirements, including SOX or equivalent
  • Strong communication and collaboration skills, with the ability to operate as a senior technical voice across engineering and business stakeholders

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