Senior Big Data Engineer — Remote & ML Infra

Remote; San Francisco (CA); Hybrid; USD 140,000 - 200,000; 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 is seeking generalist software engineers to build fast, scalable data-driven applications and ML infrastructure that power our job marketplace. You’ll work on data pipelines, stream and batch processing, and distributed systems to connect millions of jobseekers with opportunities.

The role emphasizes writing evolvable, well-instrumented code in a complex stack, with cloud deployments and Kubernetes-based environments as core responsibilities.

Qualifications

• 5+ years of professional software development experience with a focus on big data technologies.
• Experience with Hadoop, Spark, Hive and/or other big data technologies.
• Comprehensive computer science fundamentals in coding, object-oriented programming, 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

Big data

CS fundamentals

Docker

Kubernetes

Hadoop

Spark

Hive

Education

BS/MS/PhD in Computer Science or related field

Tools

Docker

Kubernetes

Apache Kafka

Flume

NiFi

Delta Lake

HBase

Cassandra

MongoDB

Apache Beam

Apache Flink

Dataflow

Kinesis

Azure Databricks

Job description

ZipRecruiter is seeking generalist software engineers to build fast, scalable data-driven applications and ML infrastructure that power our job marketplace. You’ll work on data pipelines, stream and batch processing, and distributed systems to connect millions of jobseekers with opportunities.

The role emphasizes writing evolvable, well-instrumented code in a complex stack, with cloud deployments and Kubernetes-based environments as core responsibilities.