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Data Engineer

Remote / New York / San Francisco / London
$160k - $250k
Full-time

Hiring Companies

The following companies are hiring for this role right now. Take a single OnMerit interview and top performers are shared with companies hiring now. Get offers from multiple companies from one interview.

MotherDuck
MotherDuck
Chalk
Chalk
Modal
Modal
Dagster
Dagster
Materialize
Materialize

About the Role

The modern data stack is evolving. We are looking for engineers who can move beyond batch processing to build real-time, event-driven data platforms. You will work with companies that are redefining how data is ingested, processed, and served for AI/ML applications. You will architect low-latency pipelines, optimize lakehouse performance, and build the foundation for predictive analytics and autonomous agents.

What You'll Do

  • Architect real-time data platforms for AI/ML workloads.
  • Optimize query performance and storage costs at petabyte scale.
  • Build developer-friendly data tools and self-service infrastructure.
  • Ensure data freshness, accuracy, and compliance (GDPR/CCPA).
  • Collaborate with ML engineers to deploy feature stores and inference pipelines.

Requirements

  • Proficiency in Python, Scala, or Rust for high-performance data processing.
  • Experience with streaming technologies (Kafka, Flink, Spark Streaming).
  • Deep understanding of OLAP databases (ClickHouse, DuckDB, Snowflake).
  • Ability to design and implement robust data contracts and quality checks.
  • Familiarity with modern orchestration (Dagster, Temporal) and IaC.

The Interview

This track requires just one 30-minute interview. Here's what you can expect:

  • Resume Deep Dive: Detailed walkthrough of your past experience.
  • Technical Case Study: Short case study on a technical topic.
  • Operating Case Study: Short case study on an operating topic.

Application Process

01

Upload Resume

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02

Take Interview

Complete a single 30-minute AI technical interview session

03

Get Offers

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04

Get Feedback

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