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Senior Business Intelligence Engineer

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Remote

Senior Business Intelligence Engineer

ZipRecruiter

Senior Business Intelligence Engineer

Skills

SQL QueriesBig DataPythonSnowflakeDatabricksGitData AnalysisAIScaladbtPySpark

1 month ago

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Important information


Salary:

$125,000 – $165,000 / year

Location:

United States

Work mode:

Remote

Published on:

26 September 2026

What they need


Who you are

  • 5+ years as a Data Engineer, analytics/BI Engineer or in a similar role at a senior IC level
  • Advanced SQL and deep proficiency in data modeling, schema design, and query optimization
  • Strong grasp of data warehouse architecture and modern modeling methodologies
  • Hands-on experience applying software engineering practices to data work: Git, CI/CD, code review, automated testing, monitoring
  • Proficiency with cloud-based data platforms (Redshift, Snowflake, Databricks, BigQuery, or similar)
  • Strong communicator who is comfortable working across both business stakeholders and engineering teams
  • Experience building or extending internal AI/LLM-powered tooling for analytics or developer workflows
  • Expertise with Spark (PySpark or Scala) and big data environments such as Delta Lake or Data Lake
  • Production-level proficiency with dbt and the modern data stack
  • Production-grade Python — beyond scripting, into shared libraries, services, or pipelines
  • A platform engineering mindset — building tools and abstractions that make others more productive

What the job involves

  • Design the data systems, models, and AI-powered tooling that scale how ZipRecruiter operates and makes decisions, partnering with RevOps, Decision Science, Product, and Engineering teams
  • Lead the design and implementation of data systems that serve both our operational business stakeholders (RevOps, Decision Science) and our product and engineering teams
  • Contribute to and help shape the future of our internal AI platform, impacting every analysis we run
  • Bring software engineering rigor to data work: testing, CI/CD, code review, version control, observability and evangelize these practices across the team
  • Translate complex, cross-domain business questions into robust, well-tested, reusable data sets and models
  • Collaborate directly with engineering teams to embed analytical and data-modeling capabilities into product systems and pipelines
  • Coach teammates, raise the technical bar, and help establish standards that scale beyond any single project

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