Engineering Manager: Data Pipelines & Real-Time ML

ZipRecruiter; San Francisco (CA); Hybrid; USD 200,000 - 265,000; Full time

Benefits offered by this job

Competitive compensation

Exceptional benefits package

Flexible Vacation & Paid Time Off

Employer-matched 401(k)

Job summary

ZipRecruiter’s Recommendations Ecosystem Group seeks an Engineering Manager to guide a senior team of engineers in modernizing data pipelines, storage, and access methods while strengthening data quality and security systems.

You will partner with product managers and data scientists to balance requests, set priorities, and deliver scalable, real-time data solutions for personalized job recommendations.

Qualifications

• 5+ years of professional software development experience.
• 2+ years of experience as a software engineering leader.
• Deep experience with modern big data frameworks (e.g. Spark, Hadoop, Hive).
• Streaming technologies (Kafka, Flink, Beam).
• Strong CS fundamentals (data structures, algorithms) and coding skills.
• Experience with containerization technologies like Docker and Kubernetes.
• Experience working on a B2C or B2B Product.
• Role requires communicating with Product Managers to solve problems and translate to engineering.
• Must handle messy/unreliable data (third party data sets, migrations).

Responsibilities

• Lead, mentor, and unblock a senior team of 5 engineers focused on ingestion pipelines and data stores.
• Oversee rebuild of the job ingestion pipeline and data exposure to consumer teams.
• Prioritize data quality improvements and handling of low-structure content.
• Own improvements to fraud detection and blocking mechanisms.
• Collaborate with Product Manager, Data Scientists, and other engineers to align roadmap.

Skills

5+ years of software development

2+ years as engineering leader

Strong CS fundamentals

Curious problem solver

Tools

Spark

Hadoop

Hive

Kafka

Flink

Beam

Docker

Kubernetes

Job description

ZipRecruiter’s Recommendations Ecosystem Group seeks an Engineering Manager to guide a senior team of engineers in modernizing data pipelines, storage, and access methods while strengthening data quality and security systems.

You will partner with product managers and data scientists to balance requests, set priorities, and deliver scalable, real-time data solutions for personalized job recommendations.