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.
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Work setup: Unconfirmed
Employment: Full-time — employment source
Employment type Full-time
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What you’ll bring

All qualifications

Core 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.

Tools in this posting

Python
SQL
AWS
Azure
Delta
Docker
Google Cloud (GCP)
Hadoop
Hive
Iceberg
Kafka
Kubernetes
MLflow
NoSQL
Redshift
Snowflake
Spark
Airflow
NumPy
pandas
PySpark
PyTorch
TensorFlow
BigQuery
Trino
scikit-learn

Source

- 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.

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.

Job description

View original posting ↗

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

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Source & posting history

View original posting ↗

Source notes

Source excerpts

Selected 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.

Open source at jobs.lever.co ↗Read the full description ↓

Status in our records: Active
First seen by us: Sep 22, 2026
Recorded sightings: 4
Last seen by us: Oct 8, 2026
Employer says posted: Sep 18, 2026

These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.

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