Engineering Manager, Big Data

Quick Facts

• Role: Engineering Manager, Big Data

• Work style: Hybrid (US-based roles may be remote)

Description

Lead an experienced engineering team building job ingestion pipelines, data stores, and the job understanding intelligence that powers job matching. You will modernize core data pipelines, storage, and access methods; improve data quality and security; and enhance fraud detection/blocking for low-structure, user-generated content. Partner with engineering stakeholders, data scientists, and a dedicated product manager to scale real-time job understanding.

Responsibilities

• Lead, mentor, and unblock a senior team of 5 engineers

• Rebuild the job ingestion pipeline and refine how job data is exposed to consuming teams

• Improve underlying input data quality and handle messy/unreliable data

• Own improvements to fraud detection and blocking mechanisms

• Collaborate with engineering stakeholders, data scientists, and a product manager to balance requests and roadmap priorities

• Scale data pipelines for both performance and maintainability to support scalable real-time personalization

Requirements

• 5+ years of professional software development experience

• 2+ years of experience as a software engineering leader

• Deep experience with modern big data frameworks (Spark, Hadoop, Hive)

• Experience with streaming technologies (Kafka, Flink, Beam)

• Strong CS fundamentals (data structures, algorithms) and coding skills

• Experience with containerization technologies (Docker, Kubernetes)

• Experience working on a B2C or B2B Product

• Experience dealing with messy/unreliable data (third-party datasets, data integrations, migrations)

Benefits

• Competitive compensation

• Exceptional benefits package

• Flexible vacation and paid time off

• Employer-matched 401(k)

Compensation

US base salary range (full-time): $200,000 - $265,000.