Engineering Manager, Real-Time Data Pipelines

ZipRecruiter; Seattle (WA); 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) plan

Job summary

ZipRecruiter in Seattle is seeking an Engineering Manager to lead our Recommendations Ecosystem engineering team.

You will modernize data pipelines, storage, and access methods while improving data quality and security, with a focus on real-time, scalable solutions.

Join a hybrid role that blends hands-on leadership with collaboration across product, data science, and other engineering teams.

Qualifications

• 5+ years of professional software development experience.
• 2+ years as a software engineering leader.
• Deep experience with Spark, Hadoop, Hive.
• Streaming technologies such as Kafka, Flink, Beam.
• Containerization with Docker and Kubernetes.
• Experience working on a B2C or B2B product.
• Ability to work with messy/unreliable data and data migrations.

Responsibilities

• Lead and mentor a senior team of engineers responsible for core job ingestion pipelines and data stores.
• Oversee the rebuild of the job ingestion pipeline and exposure of data to consuming teams.
• Prioritize improvements to data quality and low-structure data handling.
• Own and lead enhancements to fraud detection and blocking mechanisms.
• Collaborate with Product Manager, Data Scientists, and other engineers to balance roadmap priorities.
• Ensure scalable real-time data processing across pipelines and systems.

Skills

Software dev

Engineering lead

Big data

Streaming tech

Docker & Kubernetes

Product experience

Messy data

B2C/B2B

Job description

ZipRecruiter in Seattle is seeking an Engineering Manager to lead our Recommendations Ecosystem engineering team.

You will modernize data pipelines, storage, and access methods while improving data quality and security, with a focus on real-time, scalable solutions.

Join a hybrid role that blends hands-on leadership with collaboration across product, data science, and other engineering teams.