Pay
In line with similar jobs
$108K–$195K against $127K–$190K, the middle half of what similar US postings state.
From 2,160 postings in the last year. Stated ranges, not salaries paid.
Senior Data Engineer
6314 Remote/Teleworker US
Actively hiring, first seen by us 1 day ago- Pay
$107,900–195,050/yearAnnual period assumed — pay source
Pay Range: Pay Range $107,900.00 - $195,050.00 The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
Read the full posting- Work setting
Remote — work setting source
Listed location: 6314 Remote/Teleworker US
Read the full posting- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingDesign reusable ingestion, transformation, orchestration, and validation frameworks
Lead shared pipeline templates, data-quality gates, and lineage instrumentation
Optimize cloud data processing for performance, reliability, and cost
Troubleshoot cross-platform failures and coordinate root-cause analysis and rollback
Mentor engineers and promote reuse of common engineering capabilities
From the employer’s posting
Design and implement reusable data ingestion, transformation, orchestration, and validation frameworks
Lead engineering of shared pipeline templates, data-quality gates, lineage instrumentation
Optimize cloud data processing, partitioning, performance, reliability, and cost
Troubleshoot complex cross-platform failures and data-quality issues; coordinate root-cause analysis, remediation, rollback
Mentor engineers and coordinate with customer-requested engineering teams to promote adoption and reuse of common capabilities
What you’ll bring
All qualificationsCore experience
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical discipline and 10+ years of relevant experience, including demonstrated expertise designing and implementing complex data engineering solutions.
- Hands-on experience developing and troubleshooting production data ingestion, ETL/ELT, transformation, and validation pipelines using SQL and Python.
- Experience with cloud-based data platforms and services in Microsoft Azure, AWS, or Google Cloud; understanding of storage, orchestration, and secure data access.
- Experience with data modeling, source-to-target reconciliation, data quality testing, and pipeline monitoring or incident troubleshooting.
- Ability to document technical designs, data flows, dependencies, and operational procedures and collaborate with engineers, analysts, and data owners.
- Demonstrated experience designing reusable production data engineering frameworks or shared services and independently resolving complex integration and performance issues.
Preferred experience
- Experience with production-scale Spark/Databricks or Delta Lake processing and platform-wide performance or cost optimization.
- Experience mentoring engineers or coordinating shared engineering capabilities across multiple delivery teams.
- Familiarity with Delta Lake/lakehouse architectures, data catalogs and lineage, and governance tools such as Collibra, Immuta, or Starburst.
- Experience supporting federal IT systems and complying with security, privacy, and data-access requirements.
Qualification wording
Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical discipline and 10+ years of relevant experience, including demonstrated expertise designing and implementing complex data engineering solutions.
Hands-on experience developing and troubleshooting production data ingestion, ETL/ELT, transformation, and validation pipelines using SQL and Python.
Experience with cloud-based data platforms and services in Microsoft Azure, AWS, or Google Cloud; understanding of storage, orchestration, and secure data access.
Experience with data modeling, source-to-target reconciliation, data quality testing, and pipeline monitoring or incident troubleshooting.
Ability to document technical designs, data flows, dependencies, and operational procedures and collaborate with engineers, analysts, and data owners.
Demonstrated experience designing reusable production data engineering frameworks or shared services and independently resolving complex integration and performance issues.
Experience with production-scale Spark/Databricks or Delta Lake processing and platform-wide performance or cost optimization.
Experience mentoring engineers or coordinating shared engineering capabilities across multiple delivery teams.
Familiarity with Delta Lake/lakehouse architectures, data catalogs and lineage, and governance tools such as Collibra, Immuta, or Starburst.
Experience supporting federal IT systems and complying with security, privacy, and data-access requirements.
Education & alternatives
Required Qualifications - Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical discipline and 10+ years of relevant experience, including demonstrated expertise designing and implementing complex data engineering solutions. - Hands-on experience developing and troubleshooting production data ingestion, ETL/ELT, transformation, and validation pipelines using SQL and Python.
Posting record
Report an errorActively hiringFirst seen by us 1 day ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 7, 20261 day ago
- Recorded sightings
- 1
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 1
Early. Similar jobs usually come down between day 6 and day 54.
At Leidos, jobs usually come down by about day 27.
From 11,508 similar postings that came down, and 284 of Leidos’s. Coming down is not always a hire.
Leidos is hiring
44 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Data Engineer hiring is steady
- Takes jobs down at a usual pace
- 18% of open jobs were reposted
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- AWS
- Azure
- Databricks
- Delta Lake
- Spark
- GCP
Where the posting names them
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical discipline and 10+ years of relevant experience, including demonstrated expertise designing and implementing complex data engineering solutions. - Hands-on experience developing and troubleshooting production data ingestion, ETL/ELT, transformation, and validation pipelines using SQL and Python. - Experience with cloud-based data platforms and services in Microsoft Azure, AWS, or Google Cloud; understanding of storage, orchestration, and secure data access.
- Hands-on experience developing and troubleshooting production data ingestion, ETL/ELT, transformation, and validation pipelines using SQL and Python. - Experience with cloud-based data platforms and services in Microsoft Azure, AWS, or Google Cloud; understanding of storage, orchestration, and secure data access. - Experience with data modeling, source-to-target reconciliation, data quality testing, and pipeline monitoring or incident troubleshooting.
- Experience supporting federal IT systems and complying with security, privacy, and data-access requirements. - Experience with Agile delivery and relevant cloud/data engineering certifications. such as Microsoft Certified: Azure Data Engineer Associate, Databricks Certified Data Engineer Professional, AWS Certified Data Engineer – Associate, or equivalent. If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo — because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 — and moving faster than anyone else dares.
- Experience mentoring engineers or coordinating shared engineering capabilities across multiple delivery teams. - Hands-on Microsoft Azure data engineering experience, including Azure Data Factory, Azure Data Lake Storage, Azure Databricks, Spark, or comparable services. - Familiarity with Delta Lake/lakehouse architectures, data catalogs and lineage, and governance tools such as Collibra, Immuta, or Starburst.
- Highly Preferred: Direct, hands-on experience supporting the VA Summit Data Platform is highly preferred; experience with other VA enterprise data and analytics environments is also valuable. - Experience with production-scale Spark/Databricks or Delta Lake processing and platform-wide performance or cost optimization. - Experience mentoring engineers or coordinating shared engineering capabilities across multiple delivery teams.
- Hands-on Microsoft Azure data engineering experience, including Azure Data Factory, Azure Data Lake Storage, Azure Databricks, Spark, or comparable services. - Familiarity with Delta Lake/lakehouse architectures, data catalogs and lineage, and governance tools such as Collibra, Immuta, or Starburst. - Experience supporting federal IT systems and complying with security, privacy, and data-access requirements.
Your next step
Complete your application on leidos.wd5.myworkdayjobs.com. The employer’s form will show what is required.
Applying through Workday
- You create an account with each employer before you can upload anything. Every Workday employer has its own account, so one sign-up doesn’t carry over.
- “Autofill with Resume” comes right after sign-in, before the My Information and My Experience steps. Check every field it fills in those steps, since that’s what recruiters see.
- Your application status lives in that employer’s Candidate Home, under the same sign-in.
Already applied? Track this application
Has Leidos posted this job before?
Yes. We’ve followed 2 other Senior Data Engineer jobs there since August 2026. One came down after 4 days. One is still up.
About Leidos
- People
- About 37,274 in 2024.Benefit plan filings (Form 5500)
- Company
- Listed as LDOS.
- H-1B visas
- 22 approved for new hires in fiscal 2025.US Citizenship and Immigration Services
Demand for Data Engineer roles
New Data Engineer postings at the employers we follow are up 8% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
US government figures for database architects
- Median yearly pay, May 2025
- $139,500
- Expected change, 2025 to 2035
- 9.4% more jobsagainst 3.5% for all jobs
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Job description
**This position is contingent upon contract award.**
Leidos is seeking a Senior Data Engineer to support the Department of Veterans Affairs (VA) Summit Advanced Tooling, Lakehouse, and Artificial Intelligence Services (ATLAS) program.
Remote work within CONUS is subject to VA security and system-access requirements. Must support Eastern Time collaboration and applicable production coverage. Occasional after-hours or weekend support may be required for critical outages or planned maintenance.
This role focuses on engineering reusable ingestion, transformation, quality, and automation capabilities that improve the scalability, reliability, and efficiency of the Summit Data Platform across customer workgroups.
Primary Responsibilities
- Design and implement reusable data ingestion, transformation, orchestration, and validation frameworks aligned with the Summit product roadmap and approved enterprise architecture.
- Lead engineering of shared pipeline templates, data-quality gates, lineage instrumentation, and automated deployment or recovery patterns that reduce manual effort across workgroups.
- Optimize cloud data processing, partitioning, performance, reliability, and cost; establish practical technical measures and tuning recommendations.
- Provide technical guidance on complex data integration, source parity, semantic modeling, and federated query capabilities; collaborate with architecture and governance leads.
- Integrate automated testing, observability, CI/CD, infrastructure-as-code where appropriate, and secure access controls into production data engineering workflows.
- Troubleshoot complex cross-platform failures and data-quality issues; coordinate root-cause analysis, remediation, rollback, and operational readiness.
- Maintain reusable design documentation, standards implementation guidance, runbooks, and technical decision records.
- Mentor engineers and coordinate with customer-requested engineering teams to promote adoption and reuse of common capabilities.
Required Qualifications
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical discipline and 10+ years of relevant experience, including demonstrated expertise designing and implementing complex data engineering solutions.
- Hands-on experience developing and troubleshooting production data ingestion, ETL/ELT, transformation, and validation pipelines using SQL and Python.
- Experience with cloud-based data platforms and services in Microsoft Azure, AWS, or Google Cloud; understanding of storage, orchestration, and secure data access.
- Experience with data modeling, source-to-target reconciliation, data quality testing, and pipeline monitoring or incident troubleshooting.
- Ability to document technical designs, data flows, dependencies, and operational procedures and collaborate with engineers, analysts, and data owners.
- Demonstrated experience designing reusable production data engineering frameworks or shared services and independently resolving complex integration and performance issues.
- Experience improving data engineering delivery through automation, testing, CI/CD, or standardized deployment patterns.
- Ability to obtain and maintain the required VA Public Trust suitability determination (Tier 2/Moderate Risk).
Preferred Qualifications
- Highly Preferred: Direct, hands-on experience supporting the VA Summit Data Platform is highly preferred; experience with other VA enterprise data and analytics environments is also valuable.
- Experience with production-scale Spark/Databricks or Delta Lake processing and platform-wide performance or cost optimization.
- Experience mentoring engineers or coordinating shared engineering capabilities across multiple delivery teams.
- Hands-on Microsoft Azure data engineering experience, including Azure Data Factory, Azure Data Lake Storage, Azure Databricks, Spark, or comparable services.
- Familiarity with Delta Lake/lakehouse architectures, data catalogs and lineage, and governance tools such as Collibra, Immuta, or Starburst.
- Experience supporting federal IT systems and complying with security, privacy, and data-access requirements.
- Experience with Agile delivery and relevant cloud/data engineering certifications. such as Microsoft Certified: Azure Data Engineer Associate, Databricks Certified Data Engineer Professional, AWS Certified Data Engineer – Associate, or equivalent.
If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo — because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 — and moving faster than anyone else dares.
Original Posting:
November 6, 2026For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.
Pay Range:
Pay Range $107,900.00 - $195,050.00The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Pay Range: Pay Range $107,900.00 - $195,050.00 The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
- Location & working pattern
6314 Remote/Teleworker US
Leidos is seeking a Senior Data Engineer to support the Department of Veterans Affairs (VA) Summit Advanced Tooling, Lakehouse, and Artificial Intelligence Services (ATLAS) program. Remote work within CONUS is subject to VA security and system-access requirements. Must support Eastern Time collaboration and applicable production coverage. Occasional after-hours or weekend support may be required for critical outages or planned maintenance. This role focuses on engineering reusable ingestion, transformation, quality, and automation capabilities that improve the scalability, reliability, and efficiency of the Summit Data Platform across customer workgroups.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.