Senior Business Intelligence Engineer

Responsibilities As a Senior BI Engineer on our Business Intelligence team, you’ll sit at the intersection of data, business, and engineering - designing the data systems, models, and AI-powered tooling that scale how ZipRecruiter operates and makes decisions You’ll partner with RevOps, Decision Science, Product, and Engineering teams, working with technologies like Spark, Databricks, and Kubernetes to process billions of records daily 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 Qualifications 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 Hands-on experience applying software engineering practices to data work: Git, CI/CD, code review, automated testing, monitoring Advanced SQL and deep proficiency in data modeling, schema design, and query optimization Strong grasp of data warehouse architecture and modern modeling methodologies Proficiency with cloud-based data platforms (Redshift, Snowflake, Databricks, BigQuery, or similar) 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 #J-18808-Ljbffr