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Data Engineer Jobs Hiring Now (June 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.
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.
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.
Latest open positions
Crawled across major job boards. Click through for full details, salary, and the apply link.
Staff Data Engineer
Verkada · San Mateo, CA United States
Senior Data Platform Engineer - OLAP
Adyen · Amsterdam · Remote
Senior Staff Data Engineer - Data Stewardship
Airbnb · United States · Remote
Senior Manager, Data Engineering
Justworks · New York, New York
Senior Data Engineer
The Trade Desk · Bellevue; Seattle
Senior Data Engineer I
Samsara · Remote - Canada · Remote
Senior Data Engineer I
Samsara · Remote - US · Remote
Sr. Data Engineer (Starlink Network Analytics, Wi-Fi)
SpaceX · Redmond, WA
Senior Data Engineering Manager
YipitData · US Remote · Remote
Senior Data Platform Engineer
Pinecone · New York City · Remote
Specialist Solutions Architect - Data Engineering
Databricks · United States
Manager, Data Engineering
Justworks · New York, New York
Senior Manager, Data Engineering
Airtable · San Francisco, CA; New York, NY; Austin, TX
Revenue Operations Data Engineer( Hybrid- Bangalore)
Smartsheet · Bangalore, INDIA
Sr. Data Engineer
Cohere Health · Hyderabad, Telangana, India
Data Engineer
Asana · Warsaw
Data Engineer (Starship)
SpaceX · Starbase, TX
Data Engineer (Starlink Network Analytics, Wi-Fi)
SpaceX · Redmond, WA
Senior Data Engineer
Komodo Health · United States
Senior Data Engineer (Healthcare Data)
Komodo Health · United States
Specialist Solutions Architect - Data Engineering & Warehousing
Databricks · United States
Staff DevOps Data Engineer
Okta · Washington, DC
Data Engineer
Bringg · TLV
Data Platform Engineer
Cursor · San Francisco
Data Engineer, Marketplace
Lyft · Toronto, Canada
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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.
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