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# Business Intelligence Engineer

- **Company:** ZipRecruiter, Inc.
- **Location:** Santa Monica, CA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $125,000.0 - $165,000.0
- **Contract:** Permanent contract
- **Skills:** Automation of Tests, Big Data, BigQuery, Code Review, Continuous Integration, Data Warehousing, Python (Programming Language), Query Optimization, Software Engineering, Cloud Platform System, Sql Optimization, Large Language Models, Snowflake, Apache Spark, Git, Data Lakes, Pyspark, Software Version Control, Amazon Redshift, Databricks
- **Published:** September 19, 2026
- **Apply:** https://startup.jobs/sr-business-intelligence-engineer-ziprecruiter-10127446

## About the Role

* 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.

## Description

* Architect across business and engineering: Lead the design and implementation of data systems that serve both our operational business stakeholders (RevOps, Decision Science) and our product and engineering teams.
 * Extend our internal AI platform: Contribute to and help shape the future with work that compounds across every analysis we run at Zip.
 * Set the engineering bar for data: Bring software engineering rigor to data work: testing, CI/CD, code review, version control, observability and evangelize these practices across the team.
 * Build and own data models: Translate complex, cross-domain business questions into robust, well-tested, reusable data sets and models.
 * Partner with product engineering: Collaborate directly with engineering teams to embed analytical and data-modeling capabilities into product systems and pipelines.
 * Mentor and uplevel: Coach teammates, raise the technical bar, and help establish standards that scale beyond any single project.


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