Job description

We offer a hybrid work environment. Most US-based positions can also be performed remotely (any exceptions will be noted in the Minimum Qualifications below.) Our Mission: To actively connect people to their next great opportunity. Who We Are: ZipRecruiter is a leading online employment marketplace. Powered by AI-driven smart matching technology, the company actively connects millions of all-sized businesses and job seekers through innovative mobile, web, and email services, as well as through partnerships with the best job boards on the web. ZipRecruiter has the #1 rated job search app on iOS & Android. Summary : As a BI Engineer II 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. *We are open to leveling for this role based on experience and interview performance Key Focuses: 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. Minimum Qualifications: 3+ years as a Data Engineer, analytics/BI Engineer or in a similar role at an 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. Preferred Qualifications: 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. As part of our team you’ll enjoy: Competitive salary Exceptional benefits package Flexible Vacation & Paid Time Off Employer-matched 401(k) plan #LI-Remote The US base salary range for this full-time position is $110,000-$130,000. Our salary ranges are determined by role, level, and location, and the range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location, role-related knowledge and skills, depth of experience, relevant education or training, and additional role-related considerations. Depending on the position offered, equity, bonuses, commission, or other forms of compensation may also be provided as part of a total compensation package, in addition to a full range of medical, financial, and other benefits. ZipRecruiter is proud to be an equal opportunity employer and provides equal employment opportunities (EEO) to all employees and applicants without regard to race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity or genetics. Privacy Notice: For information about ZipRecruiter's collection and processing of job applicant personal data for this job, please see our Privacy Notice at: ziprecruiter.com

Requirements

Must-haves

We offer a hybrid work environment. Most US-based positions can also be performed remotely (any exceptions will be noted in the Minimum Qualifications below.) Our Mission:
To actively connect people to their next great opportunity.
We are open to leveling for this role based on experience and interview performance
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.
3+ years as a Data Engineer, analytics/BI Engineer or in a similar role at an 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.
Competitive salary
Exceptional benefits package

Nice-to-haves

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.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aikubernetesci/cdsqlllmpython

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

401(K)

Paid Time Off