Data Engineering Jobs in United States
There are 5,706 open Data Engineering jobs in United States on freehire right now. 1,407 of them were posted recently. The skills employers ask for most often are analytics, cloud and sql.
Salary
| Currency | Period | 25th | Median | 75th | Postings |
|---|---|---|---|---|---|
| USD | year | $147,500 | $174,600 | $210,000 | 954 |
| USD | hour | $61 | $70 | $87 | 23 |
From postings that disclose pay. Currencies are counted separately, never converted.
Most requested skills
- analytics 53%
- cloud 52%
- sql 51%
- data-engineering 51%
- python 50%
- data-pipelines 46%
- ai 45%
- data-quality 39%
How the work is done
- Remote 985 · 17%
- Hybrid 783 · 14%
- Onsite 287 · 5%
Visa sponsorship offered in 32% of the 1,004 postings that state a position on it.
Seniority
- Senior 1,663
- Lead 484
- Staff 250
- Principal 166
- C-level 122
- Junior 76
Who is hiring
- 1000+ employees 1,124
- 501-1000 employees 498
- 51-200 employees 120
- 11-50 employees 80
- 201-500 employees 25
- 1-10 employees 6
Sr. Data Engineer
Build and scale enterprise data pipelines for retail analytics and AI/ML, integrating POS, ecommerce, and third-party data to power modeling and executive decisions.
Cloud Data Platform Engineer
Designs and operates a secure, scalable cloud data platform (Databricks, Snowflake, Azure/AWS) to power analytics and AI for a global wealth-management and asset-servicing firm.
Sr. Data Engineer
Build and maintain scalable cloud-based data pipelines and warehouses to integrate healthcare data, using tools like Spark, Airflow, and BigQuery.
Head of Data Engineering
Lead Aviva’s enterprise data strategy and build a modern cloud data platform (Snowflake, Kafka, dbt) to power underwriting, financial reporting, and AI across the U.S. specialty insurance business.
Lead Data Engineer - Enterprise Data & Analytics - Remote
Lead the design and development of scalable data pipelines and analytics platforms for a large healthcare provider, using Python, SQL, Spark, and cloud technologies.
Principal Data Engineer - Enterprise Data & Analytics - Remote
Principal Data Engineer at Mayo Clinic designs and builds enterprise-scale data pipelines and analytics platforms using Python, SQL, Spark, and cloud tools to support healthcare analytics and ML workloads.
Data Governance & Quality Engineer
Build and maintain Agilent’s data governance and quality framework, ensuring trusted, discoverable data assets in Microsoft Fabric and Snowflake to support analytics and AI use cases.
Sr. Data Engineer
Designs and builds scalable data pipelines and database architectures for healthcare analytics using Python, SQL, Spark, and Snowflake/Databricks to enable advanced data-driven insights.
Data Engineering Leader
Leads a team of data engineers to design, build, and maintain enterprise data pipelines (Databricks/Azure) for POS and commercial data, ensuring quality, SLAs, and operational health while collaborating with architects and BI teams.
Staff Engineer - Data Engineering
Build and evolve a cloud-native data platform for Zelle, solving large-scale distributed data challenges and enabling payments analytics and AI/ML workloads using AWS technologies.
Senior SIEM Data Engineer
Build and maintain scalable security telemetry pipelines, onboarding diverse enterprise logs into Splunk and Databricks to power threat detection and incident response for a global financial firm.
AVP, Data Engineering and AI Innovation
Lead data engineering and AI teams to modernize Safelite’s enterprise data platform, build governed AI-enabled analytics, and empower business users with trusted, self-service insights.
Data Engineering Systems Engineering Scientist
Designs and engineers data-intensive systems for GNSS data pipelines, including requirements, architectures, and Agile delivery for government research projects.
GMP Data Governance Lead
Lead data governance for GMP compliance at a biopharma company, designing training programs and fostering a culture of data integrity across manufacturing sites.
Engineer 2, Data Engineering
Build and maintain data pipelines and warehouses to feed analytics and ML models, using Teradata, Databricks, Kubernetes, AWS S3/Redshift, and minIO.