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20 open Data Engineer jobs

Real, currently-open Data Engineer roles synced directly from company career pages. Upload your resume to see which of these match your skills, or browse all open roles. New to the role? Read our Data Engineer guide.

Hiring snapshot for Data Engineer

The most common locations right now are Remote - USA (2), United States (2), New York, NY (1). 6 of these 20 roles (30%) list a remote option. 12 were posted in the last two weeks. By team, the biggest groups are Engineering (20).

Computed from the 20 open listings shown below.

Guide: working as a Data Engineer

Data engineers build and run the pipelines that move data from source systems into warehouses and lakes where analysts and models can use it. Work includes ingestion, transformation, scheduling, schema evolution, data-quality checks and keeping storage and compute costs under control as volumes grow.

Core skills employers look for

  • Advanced SQL and data modelling
  • Python for pipelines
  • Batch and streaming processing
  • Orchestration (Airflow or similar)
  • Warehouse and lakehouse concepts
  • Kafka or another event stream
  • Data quality tests and monitoring
  • Cloud storage and access control

How to stand out when you apply

  • Build a pipeline that ingests a public API on a schedule, lands raw data, transforms it into tested tables and feeds a simple report, with the orchestration code in the repo.
  • Explain your modelling choices, such as a star schema, slowly changing dimensions or partitioning by date, and how they made downstream queries cheaper or simpler.
  • Show that you design for reruns: idempotent loads, backfills, and alerts when row counts or freshness look wrong, since broken data is often discovered late.
  • Add a small streaming component with Kafka or a managed queue to show you understand ordering, late-arriving events and at-least-once delivery.

What the interviews usually cover

Interviews typically include heavy SQL, a Python coding exercise, and a pipeline design discussion where you choose batch or streaming, plan for failures and model the target tables. Expect questions on partitioning, file formats, duplicates and upstream schema changes. Senior candidates are often asked about cost, lineage and making data trustworthy for many consumers.

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