Pay
In line with similar jobs
$131K–$237K against $127K–$190K, the middle half of what similar US postings state.
From 2,229 postings in the last year. Stated ranges, not salaries paid.
Senior Data Engineer
Gaithersburg, MD
Live, first seen by us 40 days ago- Pay
$131,300–237,350/yearAnnual period assumed — pay source
Pay Range: Pay Range $131,300.00 - $237,350.00 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
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
Before you apply
- Work authorization
- US citizens only
US citizenship is required per contract
What you’ll work on
Full postingLead architecture and build a hybrid analytical query platform
Design and implement data lakehouse architectures on object storage
Develop batch and streaming data pipelines
Integrate PostgreSQL/Aurora transactional data with analytical platforms
Mentor engineers and lead design reviews
From the employer’s posting
Lead the architecture and implementation of a hybrid analytical query platform supporting large-scale operational and analytical data.
Design and implement modern data lakehouse architectures using object storage, relational databases, and distributed analytical technologies.
Develop scalable batch and streaming data pipelines for ingestion, transformation, enrichment, and delivery of data.
Integrate PostgreSQL/Aurora transactional data with analytical and object-storage platforms.
Provide technical leadership, architecture guidance, design reviews, and mentoring engineers to implementing the data platform.
What you’ll bring
All qualificationsCore experience
- 12+ years of relevant software, data engineering, or data architecture experience, with demonstrated progression into senior technical or architecture responsibilities.
- Strong experience with PostgreSQL and/or Amazon Aurora PostgreSQL.
- Experience with Amazon S3 and object-storage-based data architectures.
- Hands-on experience with modern lakehouse technologies such as Apache Iceberg, Databricks/Delta Lake, Snowflake, Redshift, or equivalent.
- Experience designing hybrid architecture spanning relational, columnar, object-storage, and distributed analytical systems.
- Experience with distributed query engines such as Trino/Presto or equivalent technologies.
Preferred experience
- Experience with AWS-managed data services, particularly S3, Aurora PostgreSQL, Redshift, ECS/Fargate, Lambda, and related services.
- Experience with Kubernetes and container orchestration.
- Experience with data catalogs and metadata platforms such as OpenMetadata, AWS Glue Data Catalog, or equivalent.
- Experience working with geospatial, telemetry, operational, or other high-volume datasets.
Qualification wording
12+ years of relevant software, data engineering, or data architecture experience, with demonstrated progression into senior technical or architecture responsibilities.
Strong experience with PostgreSQL and/or Amazon Aurora PostgreSQL.
Experience with Amazon S3 and object-storage-based data architectures.
Hands-on experience with modern lakehouse technologies such as Apache Iceberg, Databricks/Delta Lake, Snowflake, Redshift, or equivalent.
Experience designing hybrid architecture spanning relational, columnar, object-storage, and distributed analytical systems.
Experience with distributed query engines such as Trino/Presto or equivalent technologies.
Experience with AWS-managed data services, particularly S3, Aurora PostgreSQL, Redshift, ECS/Fargate, Lambda, and related services.
Experience with Kubernetes and container orchestration.
Experience with data catalogs and metadata platforms such as OpenMetadata, AWS Glue Data Catalog, or equivalent.
Experience working with geospatial, telemetry, operational, or other high-volume datasets.
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 2, 202640 days ago
- Recorded sightings
- 93
- Last seen by us
- Nov 11, 2026
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 40
Similar jobs usually come down between day 6 and day 55.
At Leidos, jobs usually come down by about day 27.
From 13,018 similar postings that came down, and 307 of Leidos’s. Coming down is not always a hire.
Leidos is hiring
41 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Data Engineer hiring is picking up
- Takes jobs down at a usual pace
- 20% 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
- Databricks
- dbt
- Delta Lake
- Docker
- Iceberg
- Kafka
- Kubernetes
- PostgreSQL
- Redshift
- S3
- Snowflake
- Spark
- Trino
- Airflow
- Dagster
Where the posting names them
- Expert-level experience designing and implementing large-scale data architectures, lakehouses, or analytical data platforms. - Strong hands-on experience with SQL and Python. - Strong experience with PostgreSQL and/or Amazon Aurora PostgreSQL.
Key Technologies Critical: SQL, Python, PostgreSQL/Aurora PostgreSQL, Amazon S3, Apache Iceberg/lakehouse architecture, distributed analytical querying, Trino/Presto, data modeling, query optimization Strongly Desired: Redshift, Kafka, Spark, Airflow/Dagster/dbt, Docker, Kubernetes, AWS, Infrastructure as Code, Git-based CI/CD
Preferred Qualifications: - Experience with AWS-managed data services, particularly S3, Aurora PostgreSQL, Redshift, ECS/Fargate, Lambda, and related services. - Experience with Kubernetes and container orchestration.
- Experience with Kubernetes and container orchestration. - Experience with data catalogs and metadata platforms such as OpenMetadata, AWS Glue Data Catalog, or equivalent. - Experience working with geospatial, telemetry, operational, or other high-volume datasets.
Critical: SQL, Python, PostgreSQL/Aurora PostgreSQL, Amazon S3, Apache Iceberg/lakehouse architecture, distributed analytical querying, Trino/Presto, data modeling, query optimization Strongly Desired: Redshift, Kafka, Spark, Airflow/Dagster/dbt, Docker, Kubernetes, AWS, Infrastructure as Code, Git-based CI/CD Nice to Have: OpenMetadata/Glue Data Catalog, Flink, Databricks/Delta Lake, Snowflake, geospatial data experience
- Experience with Amazon S3 and object-storage-based data architectures. - Hands-on experience with modern lakehouse technologies such as Apache Iceberg, Databricks/Delta Lake, Snowflake, Redshift, or equivalent. - Experience designing hybrid architecture spanning relational, columnar, object-storage, and distributed analytical systems.
Strongly Desired: Redshift, Kafka, Spark, Airflow/Dagster/dbt, Docker, Kubernetes, AWS, Infrastructure as Code, Git-based CI/CD Nice to Have: OpenMetadata/Glue Data Catalog, Flink, Databricks/Delta Lake, Snowflake, geospatial data experience #NSBA
- Experience with distributed query engines such as Trino/Presto or equivalent technologies. - Experience building batch and/or streaming data pipelines using technologies such as Apache Kafka, Spark, Flink, Airflow, Dagster, dbt, or equivalent. - Strong understanding of data modeling, partitioning, indexing, cataloging, schema evolution, and query optimization.
- Strong understanding of data modeling, partitioning, indexing, cataloging, schema evolution, and query optimization. - Experience with Docker/containerized services and modern cloud-native architectures. - Experience with Infrastructure as Code and Git-based CI/CD.
- Design and optimize distributed query capabilities using technologies such as Trino/Presto or equivalent. - Develop solutions using Amazon S3, Apache Iceberg, Redshift, and other modern cloud data services. - Support data governance, metadata management, lineage, access controls, and security requirements.
- Experience with AWS-managed data services, particularly S3, Aurora PostgreSQL, Redshift, ECS/Fargate, Lambda, and related services. - Experience with Kubernetes and container orchestration. - Experience with data catalogs and metadata platforms such as OpenMetadata, AWS Glue Data Catalog, or equivalent.
- Design data models, partitioning strategies, indexing approaches, catalogs, and query architectures optimized for large datasets. - Integrate PostgreSQL/Aurora transactional data with analytical and object-storage platforms. - Design and optimize distributed query capabilities using technologies such as Trino/Presto or equivalent.
- Strong hands-on experience with SQL and Python. - Strong experience with PostgreSQL and/or Amazon Aurora PostgreSQL. - Experience with Amazon S3 and object-storage-based data architectures.
- Strong experience with PostgreSQL and/or Amazon Aurora PostgreSQL. - Experience with Amazon S3 and object-storage-based data architectures. - Hands-on experience with modern lakehouse technologies such as Apache Iceberg, Databricks/Delta Lake, Snowflake, Redshift, or equivalent.
- Integrate PostgreSQL/Aurora transactional data with analytical and object-storage platforms. - Design and optimize distributed query capabilities using technologies such as Trino/Presto or equivalent. - Develop solutions using Amazon S3, Apache Iceberg, Redshift, and other modern cloud data services.
- Experience designing hybrid architecture spanning relational, columnar, object-storage, and distributed analytical systems. - Experience with distributed query engines such as Trino/Presto or equivalent technologies. - Experience building batch and/or streaming data pipelines using technologies such as Apache Kafka, Spark, Flink, Airflow, Dagster, dbt, or equivalent.
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. 2 came down, usually after about 3 days.
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 7% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 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
Join Leidos and help shape the future of geospatial intelligence! We are seeking an experienced and innovative Senior Systems Engineer to support the Maru Program with our Intelligence Community customer. If you’re passionate about solving complex technical challenges, thrive in a fast-paced Agile environment, and enjoy collaborating with high-performing teams to deliver mission-critical capabilities, this is your opportunity to make a direct impact on national security.
What You'll Do
The Senior Data Engineer will lead the design and implementation of a scalable, cloud-native data architecture supporting large-scale operational and analytical workloads. This role will provide technical leadership for the development of hybrid analytical query capability, integrating relational databases, object storage, lakehouse technologies, and distributed query engines.
The ideal candidate has deep hands-on experience designing modern data platforms and can make architecture decisions around data storage, ingestion, modeling, partitioning, cataloging, governance, and query performance.
Please note Gaithersburg, MD is the program’s primary work location.
Clearance Level Required:
Active Top Secret/SCI with the ability to successfully pass a Polygraph examination.
Primary Responsibilities:
- Lead the architecture and implementation of a hybrid analytical query platform supporting large-scale operational and analytical data.
- Design and implement modern data lakehouse architectures using object storage, relational databases, and distributed analytical technologies.
- Develop scalable batch and streaming data pipelines for ingestion, transformation, enrichment, and delivery of data.
- Design data models, partitioning strategies, indexing approaches, catalogs, and query architectures optimized for large datasets.
- Integrate PostgreSQL/Aurora transactional data with analytical and object-storage platforms.
- Design and optimize distributed query capabilities using technologies such as Trino/Presto or equivalent.
- Develop solutions using Amazon S3, Apache Iceberg, Redshift, and other modern cloud data services.
- Support data governance, metadata management, lineage, access controls, and security requirements.
- Design and deploy containerized data services within cloud-native environments.
- Provide technical leadership, architecture guidance, design reviews, and mentoring engineers to implementing the data platform.
- Troubleshoot complex data, database, query-performance, infrastructure, and integration issues.
Required Qualifications:
- US citizenship is required per contract.
- 12+ years of relevant software, data engineering, or data architecture experience, with demonstrated progression into senior technical or architecture responsibilities.
- Expert-level experience designing and implementing large-scale data architectures, lakehouses, or analytical data platforms.
- Strong hands-on experience with SQL and Python.
- Strong experience with PostgreSQL and/or Amazon Aurora PostgreSQL.
- Experience with Amazon S3 and object-storage-based data architectures.
- Hands-on experience with modern lakehouse technologies such as Apache Iceberg, Databricks/Delta Lake, Snowflake, Redshift, or equivalent.
- Experience designing hybrid architecture spanning relational, columnar, object-storage, and distributed analytical systems.
- Experience with distributed query engines such as Trino/Presto or equivalent technologies.
- Experience building batch and/or streaming data pipelines using technologies such as Apache Kafka, Spark, Flink, Airflow, Dagster, dbt, or equivalent.
- Strong understanding of data modeling, partitioning, indexing, cataloging, schema evolution, and query optimization.
- Experience with Docker/containerized services and modern cloud-native architectures.
- Experience with Infrastructure as Code and Git-based CI/CD.
- Strong understanding of data security, access controls, governance, and protecting sensitive data.
Preferred Qualifications:
- Experience with AWS-managed data services, particularly S3, Aurora PostgreSQL, Redshift, ECS/Fargate, Lambda, and related services.
- Experience with Kubernetes and container orchestration.
- Experience with data catalogs and metadata platforms such as OpenMetadata, AWS Glue Data Catalog, or equivalent.
- Experience working with geospatial, telemetry, operational, or other high-volume datasets.
- Experience designing platforms supporting both interactive queries and large-scale analytical workloads.
- Experience supporting production data platforms in classified, DoD, Intelligence Community, or other high-security environments.
- Experience providing technical directions to multidisciplinary engineering teams.
Key Technologies
Critical: SQL, Python, PostgreSQL/Aurora PostgreSQL, Amazon S3, Apache Iceberg/lakehouse architecture, distributed analytical querying, Trino/Presto, data modeling, query optimization
Strongly Desired: Redshift, Kafka, Spark, Airflow/Dagster/dbt, Docker, Kubernetes, AWS, Infrastructure as Code, Git-based CI/CD
Nice to Have: OpenMetadata/Glue Data Catalog, Flink, Databricks/Delta Lake, Snowflake, geospatial data experience
#NSBA
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:
October 1, 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 $131,300.00 - $237,350.00The 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 $131,300.00 - $237,350.00 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
Gaithersburg, MD
What You'll Do The Senior Data Engineer will lead the design and implementation of a scalable, cloud-native data architecture supporting large-scale operational and analytical workloads. This role will provide technical leadership for the development of hybrid analytical query capability, integrating relational databases, object storage, lakehouse technologies, and distributed query engines. The ideal candidate has deep hands-on experience designing modern data platforms and can make architecture decisions around data storage, ingestion, modeling, partitioning, cataloging, governance, and query performance.
More source context
Primary Responsibilities: - Lead the architecture and implementation of a hybrid analytical query platform supporting large-scale operational and analytical data. - Design and implement modern data lakehouse architectures using object storage, relational databases, and distributed analytical technologies.
More relevant text appears in the full description.
- Work authorization
Required Qualifications: - US citizenship is required per contract. - 12+ years of relevant software, data engineering, or data architecture experience, with demonstrated progression into senior technical or architecture responsibilities.