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Business Intelligence Engineer

ZipRecruiter

Skills

Required

  • AI / LLM-powered
  • data warehouse architecture
  • SQL
  • data modeling
  • cloud-based data platforms
  • modern modeling methodologies
  • schema design
  • query optimization
  • Redshift
  • Snowflake
  • Databricks
  • BigQuery
  • Spark
  • PySpark / Scala

Preferred

  • software engineering
  • Git
  • CI/CD
  • code review
  • automated testing
  • monitoring

ZipRecruiter as a Senior Business Intelligence Engineer. In this role, you will design and implement data systems that support both operational business stakeholders and product/engineering teams. You will contribute to the development of our internal AI platform and bring software engineering rigor to data work. You will also collaborate with engineering teams to embed analytical and data-modeling capabilities into product systems and pipelines. The ideal candidate will have a strong grasp of data warehouse architecture, advanced SQL proficiency, and experience with cloud-based data platforms.

Responsibilities

  • Design and implement data systems that serve operational business stakeholders and product/engineering teams.
  • Contribute to and help shape the future of the internal AI platform, impacting every analysis run.
  • Translate complex, cross-domain business questions into robust, well-tested, reusable data sets and models.

Requirements

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

Preferred

  • Hands-on experience applying software engineering practices to data work: Git, CI/CD, code review, automated testing, monitoring

Pay

USD 100,000 - 130,000

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