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Data Engineer Jobs Hiring Now (July 2026)

Data engineers build the pipelines, warehouses, and tooling that move and shape data for analytics and ML. They own ingestion, transformation, modeling, and the reliability of the data plane.

3 min read

Data Engineer market snapshot

Live from PrismCV's job catalog. Salaries reflect postings that publish a range; remote share excludes postings without a location tag.

Open roles
10
Salary low
$500
Salary median
$175k
Salary high
$300k
Remote-friendly
10%

Data engineering postings in 2026 cluster into three shapes. Analytics-platform roles build and govern the warehouse: ingestion, dbt transformation layers, modeling, and the quality tooling that keeps dashboards trustworthy. Streaming and infrastructure roles run Kafka-class systems where latency and throughput are the product. And a fast-growing third shape supports AI: feature pipelines, retrieval infrastructure, and the data plumbing behind LLM products. The title is the same; the interviews and the day-to-day are not. Read the responsibilities paragraph before deciding which resume to send.

Stack expectations are unusually standardized. Postings name dbt, an orchestrator (Airflow most commonly, Dagster rising), a cloud warehouse (Snowflake, BigQuery, Databricks), and Python plus deep SQL almost universally. Streaming roles add Kafka and a processing framework. Infrastructure-as-code and one major cloud are assumed at mid-level and above. This standardization cuts both ways: it is easy to be screened in by matching the named stack, and easy to be screened out for missing one keyword the JD treats as essential — check each posting against your resume before applying.

The discipline's center of gravity has shifted from building pipelines to operating them: postings emphasize data quality, observability, contracts with producer teams, SLAs, and cost control more than raw construction. Teams have been burned by silently wrong data and surprising warehouse bills, and they are hiring for the engineers who prevent both.

Posting red flags: a "data engineer" role that is mostly report-writing against an existing warehouse is an analyst role titled up; one that includes building the warehouse, the dashboards, and the ML models is three jobs in one posting, common at companies hiring their first data person. That first-data-hire role can be a great career accelerant — but price it as what it is.

Use the listings below as your feed. PrismCV crawls the major boards and de-duplicates across them. The live salary data above reflects what current postings advertise, and the ATS Checker scores your resume against any specific posting — particularly worth running in this discipline, where JDs are keyword-dense and screeners lean on exact stack matches.


Companies hiring data engineers now

The five companies with the most active openings in this role today.

Airtable

1 open

BlueOwl LLC

1 open

Clara

1 open

IOMED

1 open

Instacart

1 open


Latest open positions

Crawled across major job boards. Click through for full details, salary, and the apply link.

Software Engineer, Product Engineer, Data Engineer, Data Scientist, SRE

Airtable · Onsite or remote (USA only)

Recently

Senior Data Engineer

Mira ( https://mirabeauty.com ) · San Francisco

$500–$500Recently

Data Engineer

IOMED · Not specified

Recently

Sr Full-stack Engineer, Sr Data Engineer, Data Scientist, Machine Learning Engineer, Sr iOS/Android Engineer

Instacart · onsite in San Francisco

Recently

Privacy, Backend, Data Engineering, Front End, SDET, Analytics

BlueOwl LLC · San Francisco, CA or Portland, OR

Recently

Senior Data Engineer

Warby Parker · New York, NY or Remote

Recently

Senior Software Engineers (Full-stack, Backend, Frontend) & Data Engineers

Validere (YC S16) · Toronto, ON

Recently

Senior Data Engineer

Tovala · Chicago, IL

Recently

Robotics Data Engineer Consultant

Instawork · San Francisco, CA, US / Remote (US) · Remote

$50k–$300kRecently

Founding Data Engineer (Healthcare)

Clara · San Francisco, CA, US

$145k–$215kRecently

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Frequently asked questions

Demand has grown with AI rather than despite it: every LLM feature and ML system sits on pipelines someone must build and operate, and "AI-ready data" appears in an increasing share of postings. The work is shifting toward retrieval infrastructure, feature pipelines, and quality guarantees — data engineers who add those to a solid platform foundation are among the harder hires for companies to make right now.

Snowflake and BigQuery cover the widest share of postings, with Databricks strong where Spark and ML workloads dominate. Concepts transfer: partitioning, clustering, cost mechanics, and materialization strategy look similar across them, and interviewers generally accept depth in one plus literacy in the others. AWS remains the most commonly named cloud overall.

Ask how downstream teams discover and trust data today (a real lineage/catalog answer versus "they ask us"), what the worst data incident of the past year was and what changed after, and who pays the warehouse bill. The answers reveal whether the platform is an engineering discipline there or a pile of scheduled queries with a roadmap.

Score your Data Engineer resume against any of these jobs

Upload your resume once, then see your ATS match score for any job posting on the page. Free.

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