Big Data Engineering Manager — Lead, Scale & Innovate

ZipRecruiter, Inc.; United States; Remote; USD 140,000 - 190,000; Full time

Benefits offered by this job

Competitive compensation

Exceptional benefits package

Flexible vacation & PTO

Employer-matched 401(k) plan

Job summary

ZipRecruiter, Inc. is seeking a data engineering leader to own the mission and execution of a team responsible for scalable data pipelines and production-grade data systems. You will partner with product managers to align on the roadmap and remove roadblocks to accelerate delivery.

The role emphasizes building culture, coaching engineers, and driving innovation across the data and analytics platform to power AI-powered features and products.

Qualifications

• 6+ years in software development or data engineering environments.
• Experience building ETL pipelines at scale.
• 2+ years of experience as a Data Engineering leader.
• Experience designing, building, and supporting production-grade data pipelines.

Responsibilities

• Own the mission, execution, morale, and code quality of your team.
• Partner effectively with product managers to maintain and execute against the product roadmap.
• Serve as a force multiplier for your team by removing roadblocks and implementing process improvements.
• Actively build community and culture throughout the engineering organization.
• Continually develop, coach, motivate, and improve your team.
• Champion and evolve innovation and evangelize BIG ideas.

Skills

Data leadership

ETL pipelines

Data engineering

Team coaching

Roadmap collaboration

Education

BS/MS/PhD in CS/Math/Physics

Tools

SQL

Python

Spark

ETL Tools

Job description

ZipRecruiter, Inc. is seeking a data engineering leader to own the mission and execution of a team responsible for scalable data pipelines and production-grade data systems. You will partner with product managers to align on the roadmap and remove roadblocks to accelerate delivery.

The role emphasizes building culture, coaching engineers, and driving innovation across the data and analytics platform to power AI-powered features and products.