Senior Data Engineer — Scalable ML & Data Pipelines

ZipRecruiter, Inc.; Northern (KY); Hybrid; USD 130,000 - 175,000; 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, Inc. is seeking senior data engineers to build scalable data processing and ML infrastructure powering our AI-driven matching platform. The role focuses on big data tooling, cloud deployments, and distributed systems in a fast-paced environment.

Join a team working on data pipelines, Spark/Kafka/Hadoop ecosystems, and containerized services in Kubernetes. The position offers a hybrid work arrangement with remote options for many US-based roles and a strong benefits package.

Qualifications

• 2+ years of professional software development experience with a focus on Python and big data technologies.
• Experience with Spark, Kafka, Hadoop, Hive, and/or other big data technologies.
• Comprehensive CS fundamentals in coding, OOP, data structures, and algorithms.
• Experience with containerization technologies like Docker and/or Kubernetes.

Responsibilities

• Build data processing and exploration pipelines along with ML infrastructure to power our intelligence.
• Deploy a range of cloud-based technologies for critical projects.
• Write, test, instrument, and deploy code to our Kubernetes environment.
• Help drive the innovation and evolution of ZipRecruiter.

Skills

Python

Big data concepts

Data processing pipelines

Distributed systems

Education

BS/MS/PhD in Mathematics, Computer Science, Physics, related technical field or equivalent practical experience

Tools

Apache Kafka

Spark

Hadoop/Hive

Docker

Kubernetes

Apache Flink

Delta Lake

Job description

ZipRecruiter, Inc. is seeking senior data engineers to build scalable data processing and ML infrastructure powering our AI-driven matching platform. The role focuses on big data tooling, cloud deployments, and distributed systems in a fast-paced environment.

Join a team working on data pipelines, Spark/Kafka/Hadoop ecosystems, and containerized services in Kubernetes. The position offers a hybrid work arrangement with remote options for many US-based roles and a strong benefits package.