Pay
In line with similar jobs
$135K–$160K against $127K–$190K, the middle half of what similar US postings state.
From 2,133 postings in the last year. Stated ranges, not salaries paid.
Senior Data Engineer
Vienna, VA
Live, first seen by us 43 days ago- Pay
USD 135,000–160,000/year — pay source
Salary 135,000 – 160,000 USD per year SteerBridge is proud to be an Equal Opportunity Employer. We are committed to creating a diverse and inclusive workplace where all qualified applicants and employees are treated with respect and dignity—regardless of race, color, gender, age, religion, national origin, ancestry, disability, veteran status, genetic information, sexual orientation, or any other characteristic protected by law.
Read the full posting- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type Full-time
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 for this position under applicable federal contract requirements
What you’ll work on
Full postingRun data engineering work across existing systems of record and multiple databases
Improve data entry, management and extraction processes in proprietary systems
Run data quality checks to find errors and inconsistencies
Analyze data and present findings to support business and operational needs
Maintain documentation of data processes, workflows and methodologies
From the employer’s posting
Perform data engineering activities across existing systems of record and multiple databases.
Enhance and optimize data entry, management, and extraction processes to improve data usability within proprietary systems.
Conduct data quality checks to identify inconsistencies, errors, and opportunities for improvement.
Analyze data and present findings to support business and operational needs.
Maintain accurate documentation of data processes, workflows, and methodologies.
What you’ll bring
All qualificationsCore experience
- Bachelor’s degree or higher in Systems Engineering, Computer Science, Data Science, or a related field.
- 6+ years of data engineering or related experience designing, developing, and supporting production data platforms and pipelines.
- Strong proficiency with Python, SQL, Pandas, PySpark, NumPy, and Git, including experience developing reusable, testable, and performance-optimized data processing and automation solutions.
- Experience designing conceptual, logical, and physical data models and working with relational, NoSQL, data warehouse, data lake, and lakehouse architectures.
- Hands-on experience developing and orchestrating scalable batch and/or real-time data pipelines using technologies such as Apache Spark, Kafka, Airflow, NiFi, AWS Glue, Azure Data Factory, or GCP Dataflow.
- Experience developing cloud-based data solutions in AWS, Azure, and/or GCP, including cloud storage, managed databases, compute services, and modern data warehousing platforms such as Redshift, Snowflake, or BigQuery.
Preferred experience
- Experience with distributed computing and modern data lake/lakehouse technologies such as Hadoop, Spark, Hive, Presto/Trino, Delta Lake, Apache Iceberg, or Apache Hudi.
- Experience with DevOps/DataOps practices, including Infrastructure as Code (IaC), Docker, Kubernetes, Git-based workflows, automated testing, and CI/CD for data infrastructure and pipelines.
- Experience optimizing large-scale data environments for query performance, pipeline efficiency, scalability, and cloud resource utilization and cost.
- Experience developing resilient, automated data pipelines with monitoring, alerting, retry logic, failure recovery, and other self-healing capabilities.
Qualification wording
Bachelor’s degree or higher in Systems Engineering, Computer Science, Data Science, or a related field.
6+ years of data engineering or related experience designing, developing, and supporting production data platforms and pipelines.
Strong proficiency with Python, SQL, Pandas, PySpark, NumPy, and Git, including experience developing reusable, testable, and performance-optimized data processing and automation solutions.
Experience designing conceptual, logical, and physical data models and working with relational, NoSQL, data warehouse, data lake, and lakehouse architectures.
Hands-on experience developing and orchestrating scalable batch and/or real-time data pipelines using technologies such as Apache Spark, Kafka, Airflow, NiFi, AWS Glue, Azure Data Factory, or GCP Dataflow.
Experience developing cloud-based data solutions in AWS, Azure, and/or GCP, including cloud storage, managed databases, compute services, and modern data warehousing platforms such as Redshift, Snowflake, or BigQuery.
Experience with distributed computing and modern data lake/lakehouse technologies such as Hadoop, Spark, Hive, Presto/Trino, Delta Lake, Apache Iceberg, or Apache Hudi.
Experience with DevOps/DataOps practices, including Infrastructure as Code (IaC), Docker, Kubernetes, Git-based workflows, automated testing, and CI/CD for data infrastructure and pipelines.
Experience optimizing large-scale data environments for query performance, pipeline efficiency, scalability, and cloud resource utilization and cost.
Experience developing resilient, automated data pipelines with monitoring, alerting, retry logic, failure recovery, and other self-healing capabilities.
Education & alternatives
- Eligibility requirements: U.S. citizenship is required for this position under applicable federal contract requirements. Candidate must also be able to obtain and maintain a Public Trust clearance; an active Secret or Top Secret security clearance also satisfies this requirement. - Bachelor’s degree or higher in Systems Engineering, Computer Science, Data Science, or a related field. - 6+ years of data engineering or related experience designing, developing, and supporting production data platforms and pipelines.
Benefits in the posting
Full benefits wording- Health insurance
- Dental insurance
- Vision insurance
- Life Insurance
- 401(k) Retirement Plan with matching
- Paid Time Off
- Paid Federal Holidays
- SteerBridge also offers benefits that may include health and life insurance, paid time off, paid holidays, disability coverage, retirement savings, and professional development opportunities. Benefits vary by position and eligibility.
From the employer’s posting.
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Sep 22, 202643 days ago
- Recorded sightings
- 28
- Last seen by us
- Nov 4, 2026
- Employer says posted
- Sep 18, 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 43
Similar jobs usually come down between day 5 and day 54.
From 10,736 similar postings that came down. Coming down is not always a hire.
Steerbridge is hiring
17 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Data Engineer hiring has slowed
- Takes jobs down at a usual pace
- 6% 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
- BigQuery
- Delta Lake
- Docker
- GCP
- Hadoop
- Hive
- Iceberg
- Kafka
- Kubernetes
- MLflow
- NoSQL
- Redshift
- Snowflake
- Spark
- Trino
- Airflow
- NumPy
- pandas
- PySpark
- PyTorch
- scikit-learn
- TensorFlow
Where the posting names them
- 6+ years of data engineering or related experience designing, developing, and supporting production data platforms and pipelines. - Strong proficiency with Python, SQL, Pandas, PySpark, NumPy, and Git, including experience developing reusable, testable, and performance-optimized data processing and automation solutions. - Experience designing conceptual, logical, and physical data models and working with relational, NoSQL, data warehouse, data lake, and lakehouse architectures.
- Experience designing conceptual, logical, and physical data models and working with relational, NoSQL, data warehouse, data lake, and lakehouse architectures. - Hands-on experience developing and orchestrating scalable batch and/or real-time data pipelines using technologies such as Apache Spark, Kafka, Airflow, NiFi, AWS Glue, Azure Data Factory, or GCP Dataflow. - Experience developing cloud-based data solutions in AWS, Azure, and/or GCP, including cloud storage, managed databases, compute services, and modern data warehousing platforms such as Redshift, Snowflake, or BigQuery.
- Hands-on experience developing and orchestrating scalable batch and/or real-time data pipelines using technologies such as Apache Spark, Kafka, Airflow, NiFi, AWS Glue, Azure Data Factory, or GCP Dataflow. - Experience developing cloud-based data solutions in AWS, Azure, and/or GCP, including cloud storage, managed databases, compute services, and modern data warehousing platforms such as Redshift, Snowflake, or BigQuery. - Experience with data quality, governance, security, lineage, metadata management, performance optimization, CI/CD, and software engineering best practices for large-scale data environments.
Preferred Qualifications - Experience with distributed computing and modern data lake/lakehouse technologies such as Hadoop, Spark, Hive, Presto/Trino, Delta Lake, Apache Iceberg, or Apache Hudi. - Experience with DevOps/DataOps practices, including Infrastructure as Code (IaC), Docker, Kubernetes, Git-based workflows, automated testing, and CI/CD for data infrastructure and pipelines.
- Experience with distributed computing and modern data lake/lakehouse technologies such as Hadoop, Spark, Hive, Presto/Trino, Delta Lake, Apache Iceberg, or Apache Hudi. - Experience with DevOps/DataOps practices, including Infrastructure as Code (IaC), Docker, Kubernetes, Git-based workflows, automated testing, and CI/CD for data infrastructure and pipelines. - Experience optimizing large-scale data environments for query performance, pipeline efficiency, scalability, and cloud resource utilization and cost.
- Experience developing resilient, automated data pipelines with monitoring, alerting, retry logic, failure recovery, and other self-healing capabilities. - Familiarity with AI/ML data pipeline technologies such as TensorFlow, PyTorch, Scikit-learn, MLflow, Kubeflow, or feature stores. - Experience mentoring junior engineers, conducting technical reviews, and clearly documenting technical architectures using tools such as Lucidchart, PlantUML, or Draw.io.
- Strong proficiency with Python, SQL, Pandas, PySpark, NumPy, and Git, including experience developing reusable, testable, and performance-optimized data processing and automation solutions. - Experience designing conceptual, logical, and physical data models and working with relational, NoSQL, data warehouse, data lake, and lakehouse architectures. - Hands-on experience developing and orchestrating scalable batch and/or real-time data pipelines using technologies such as Apache Spark, Kafka, Airflow, NiFi, AWS Glue, Azure Data Factory, or GCP Dataflow.
Your next step
Complete your application on jobs.lever.co. The employer’s form will show what is required.
Applying through Lever
- No account needed: one form, and Lever reads your resume into the profile recruiters search.
Already applied? Track this application
Has Steerbridge posted this job before?
Yes. We’ve followed 2 other Senior Data Engineer jobs there since May 2026. One came down after 23 days. One is still up.
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
SteerBridge is a modern technology company delivering innovative, mission‑focused solutions to the U.S. Government and private sector. Leveraging deep expertise in federal acquisition, digital transformation, and emerging technologies, we deliver agile, commercial‑grade capabilities that accelerate operational effectiveness and drive measurable mission success.
At the core of SteerBridge is our people—especially the veterans whose leadership, problem‑solving mindset, and commitment to excellence elevate every project we support. We don’t simply hire exceptional talent; we cultivate it, creating meaningful career pathways for veterans, military spouses, and professionals who share our passion for advancing technology and strengthening the missions we serve.
Position Overview
SteerBridge seeks a highly skilled and motivated individual to join our team as a Senior Data Engineer to align data solutions to business requirements by planning and managing data infrastructure and strategy for our Modern Disability Claims AI/ML program. Our team is dedicated to harnessing the power of AI/ML to increase claims processing throughput and reduce adjudication wait times, ultimately improving outcomes for veterans.
Key Responsibilties
-
Perform data engineering activities across existing systems of record and multiple databases.
-
Enhance and optimize data entry, management, and extraction processes to improve data usability within proprietary systems.
-
Conduct data quality checks to identify inconsistencies, errors, and opportunities for improvement.
-
Analyze data and present findings to support business and operational needs.
-
Maintain accurate documentation of data processes, workflows, and methodologies.
-
Collaborate with team members and stakeholders to address data needs and support continuous improvement.
Required Qualifications
-
Eligibility requirements: U.S. citizenship is required for this position under applicable federal contract requirements. Candidate must also be able to obtain and maintain a Public Trust clearance; an active Secret or Top Secret security clearance also satisfies this requirement.
-
Bachelor’s degree or higher in Systems Engineering, Computer Science, Data Science, or a related field.
-
6+ years of data engineering or related experience designing, developing, and supporting production data platforms and pipelines.
-
Strong proficiency with Python, SQL, Pandas, PySpark, NumPy, and Git, including experience developing reusable, testable, and performance-optimized data processing and automation solutions.
-
Experience designing conceptual, logical, and physical data models and working with relational, NoSQL, data warehouse, data lake, and lakehouse architectures.
-
Hands-on experience developing and orchestrating scalable batch and/or real-time data pipelines using technologies such as Apache Spark, Kafka, Airflow, NiFi, AWS Glue, Azure Data Factory, or GCP Dataflow.
-
Experience developing cloud-based data solutions in AWS, Azure, and/or GCP, including cloud storage, managed databases, compute services, and modern data warehousing platforms such as Redshift, Snowflake, or BigQuery.
-
Experience with data quality, governance, security, lineage, metadata management, performance optimization, CI/CD, and software engineering best practices for large-scale data environments.
-
Preference for candidates located in the Vienna, VA area who are able to work onsite at the SteerBridge Vienna office at least three days per week. Hybrid arrangements may be available at the supervisor’s discretion.
Preferred Qualifications
-
Experience with distributed computing and modern data lake/lakehouse technologies such as Hadoop, Spark, Hive, Presto/Trino, Delta Lake, Apache Iceberg, or Apache Hudi.
-
Experience with DevOps/DataOps practices, including Infrastructure as Code (IaC), Docker, Kubernetes, Git-based workflows, automated testing, and CI/CD for data infrastructure and pipelines.
-
Experience optimizing large-scale data environments for query performance, pipeline efficiency, scalability, and cloud resource utilization and cost.
-
Experience developing resilient, automated data pipelines with monitoring, alerting, retry logic, failure recovery, and other self-healing capabilities.
-
Familiarity with AI/ML data pipeline technologies such as TensorFlow, PyTorch, Scikit-learn, MLflow, Kubeflow, or feature stores.
-
Experience mentoring junior engineers, conducting technical reviews, and clearly documenting technical architectures using tools such as Lucidchart, PlantUML, or Draw.io.
Benefits
- Health insurance
- Dental insurance
- Vision insurance
- Life Insurance
- 401(k) Retirement Plan with matching
- Paid Time Off
- Paid Federal Holidays
The posted compensation range reflects the scope and requirements of this position. A final offer will be determined based on the candidate’s relevant experience, skills, education, certifications, and work location, along with the responsibilities of the position. Where applicable, contract requirements, wage determinations, and federal contract labor categories may also inform the offer.
SteerBridge also offers benefits that may include health and life insurance, paid time off, paid holidays, disability coverage, retirement savings, and professional development opportunities. Benefits vary by position and eligibility.
Salary
135,000 – 160,000 USD per year
SteerBridge is proud to be an Equal Opportunity Employer. We are committed to creating a diverse and inclusive workplace where all qualified applicants and employees are treated with respect and dignity—regardless of race, color, gender, age, religion, national origin, ancestry, disability, veteran status, genetic information, sexual orientation, or any other characteristic protected by law.
We also provide reasonable accommodations for individuals with disabilities in accordance with applicable laws. If you require assistance during the application process, we encourage you to reach out so we can support your needs.
Employment type
Full-time
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Salary 135,000 – 160,000 USD per year SteerBridge is proud to be an Equal Opportunity Employer. We are committed to creating a diverse and inclusive workplace where all qualified applicants and employees are treated with respect and dignity—regardless of race, color, gender, age, religion, national origin, ancestry, disability, veteran status, genetic information, sexual orientation, or any other characteristic protected by law.
- Location & working pattern
Vienna, VA
- Experience with data quality, governance, security, lineage, metadata management, performance optimization, CI/CD, and software engineering best practices for large-scale data environments. - Preference for candidates located in the Vienna, VA area who are able to work onsite at the SteerBridge Vienna office at least three days per week. Hybrid arrangements may be available at the supervisor’s discretion. Preferred Qualifications
- Work authorization
Required Qualifications - Eligibility requirements: U.S. citizenship is required for this position under applicable federal contract requirements. Candidate must also be able to obtain and maintain a Public Trust clearance; an active Secret or Top Secret security clearance also satisfies this requirement. - Bachelor’s degree or higher in Systems Engineering, Computer Science, Data Science, or a related field.