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 AI/ML Maintenance, Sustainment, and Deployment Planning Project. Our team is dedicated to harnessing the power of AI/ML to increase parts availability and reduce maintenance wait times, ultimately maximizing aircraft availability. In this role, you will be responsible performing Data Engineering tasks within the existing systems of record with multiple databases. Your mission will be to enhance and optimize data entry, management and extraction within this database to ensure its usability within our proprietary system. Data management activities include performing data quality checks, analysis, presenting data and documenting the process. The ideal candidate is a quick learner, curious, innovative, results-oriented and has strong interpersonal skills Key Responsibilities Design and maintain scalable conceptual, logical, and physical data models supporting analytics, reporting, machine learning, and transactional workloads across relational, NoSQL, graph, time-series, and document-based systems. Design, build, and optimize fault-tolerant batch and real-time data pipelines using Python and distributed processing and orchestration technologies such as Kafka, Airflow, Spark, Flink, and NiFi. Architect and manage cloud-native data solutions across AWS, GCP, or Azure, including data lakes, data warehouses, lakehouse architectures, and hybrid or multi-cloud environments. Develop and optimize large-scale data platforms using technologies such as Redshift, Snowflake, BigQuery, Delta Lake, Apache Iceberg, and Apache Hudi, applying appropriate partitioning, schema evolution, and performance optimization strategies. Optimize SQL and NoSQL databases through query tuning, indexing, sharding, partitioning, replication, caching, backup, and disaster recovery strategies. Implement data governance, quality, lineage, metadata management, access controls, lifecycle policies, and security standards to support reliable and compliant data environments. Develop maintainable, production-quality Python and SQL solutions using software engineering best practices, including version control, testing, CI/CD, documentation, performance profiling, and reusable design patterns. Partner with data scientists, analysts, engineers, and business stakeholders to support ML-ready data pipelines and analytics solutions while providing technical leadership, mentoring engineers, and establishing data engineering and architecture standards. Required Qualifications Eligibility requirements: U.S. citizenship is required for this position under applicable federal contract requirements. Candidates must also be able to obtain and maintain the security clearance required for the role. Bachelor’s degree or higher in Systems Engineering, Computer Science, or a related field. 6+ years of relevant professional experience, including experience developing and supporting data pipelines using advanced analytics tools, platforms, and Python. Experience scripting, developing tools, and automating large-scale computing environments. Proficiency with Python, Pandas, PySpark, NumPy, SciPy, SQL, and Git, with familiarity in TensorFlow, PyTorch, and Scikit-learn. Location: Preference for candidates local to the Vienna, VA area who are able to work on-site at our Vienna office three or more days per week. Hybrid opportunities may be available at the supervisor’s discretion. Preferred Qualifications Experience with DevOps/DataOps practices, including infrastructure as code, Docker, Kubernetes, and automated deployment of data infrastructure. Experience with Git-based workflows, automated integration testing, and CI/CD for data pipelines. Experience optimizing query performance, pipeline efficiency, and cloud or compute resource utilization. Experience developing resilient, automated data pipelines with retry logic, monitoring, alerting, and self-healing capabilities. Ability to clearly document and communicate 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 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.

Requirements

Must-haves

Position Overview
Design, build, and optimize fault-tolerant batch and real-time data pipelines using Python and distributed processing and orchestration technologies such as Kafka, Airflow, Spark, Flink, and NiFi.
Architect and manage cloud-native data solutions across AWS, GCP, or Azure, including data lakes, data warehouses, lakehouse architectures, and hybrid or multi-cloud environments.
Optimize SQL and NoSQL databases through query tuning, indexing, sharding, partitioning, replication, caching, backup, and disaster recovery strategies.
Implement data governance, quality, lineage, metadata management, access controls, lifecycle policies, and security standards to support reliable and compliant data environments.
Develop maintainable, production-quality Python and SQL solutions using software engineering best practices, including version control, testing, CI/CD, documentation, performance profiling, and reusable design patterns.
Eligibility requirements: U.S. citizenship is required for this position under applicable federal contract requirements. Candidates must also be able to obtain and maintain the security clearance required for the role.
Bachelor’s degree or higher in Systems Engineering, Computer Science, or a related field.
6+ years of relevant professional experience, including experience developing and supporting data pipelines using advanced analytics tools, platforms, and Python.
Experience scripting, developing tools, and automating large-scale computing environments.
Proficiency with Python, Pandas, PySpark, NumPy, SciPy, SQL, and Git, with familiarity in TensorFlow, PyTorch, and Scikit-learn.
Location: Preference for candidates local to the Vienna, VA area who are able to work on-site at our Vienna office three or more days per week. Hybrid opportunities may be available at the supervisor’s discretion.

Nice-to-haves

Experience with DevOps/DataOps practices, including infrastructure as code, Docker, Kubernetes, and automated deployment of data infrastructure.
Experience with Git-based workflows, automated integration testing, and CI/CD for data pipelines.
Experience optimizing query performance, pipeline efficiency, and cloud or compute resource utilization.
Experience developing resilient, automated data pipelines with retry logic, monitoring, alerting, and self-healing capabilities.
Ability to clearly document and communicate technical architectures using tools such as Lucidchart, PlantUML, or Draw.io.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

agileaimlmachine learningpythonawsgcpazuresqlci/cddockerkubernetes

Platform: lever
Effort: quick

Benefits

Benefits detected in the listing.

Health Insurance

Dental

Vision

401(K)

Paid Time Off