Data Engineer

Vienna, VA

Aviation – C130 /

Full-time /

On-site

SteerBridge Strategies is a CVE-Verified Service-Disabled, Veteran-Owned Small Business (SDVOSB) delivering a broad spectrum of professional services to the U.S. Government and private sector. Backed by decades of hands-on experience in federal acquisition and procurement, we provide agile, best-in-class commercial solutions that drive mission success.

Our strength lies in our people—especially the veterans whose leadership, discipline, and dedication shape everything we do. At SteerBridge, we don’t just hire talent—we empower it, creating meaningful career paths for those who have served and those who share our commitment to excellence.

SteerBridge seeks highly skilled and motivated Data Engineers to join our team. We are at the forefront of applying advanced computational analytics to revolutionize supply chain management in the aerospace industry. Our team is dedicated to harnessing the power of AI/ML to increase parts availability and reduce maintenance wait times, ultimately maximizing aircraft availability and redefine operational readiness for aircraft missions.

In this role, you will be responsible for performing Data Engineering tasks on-site 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. This position also involves mentoring and collaborating with Marines at the

squadron level, requiring a deep understanding of squadron-specific operations and a commitment to improving data entry and indexing practices. As a crucial link between our existing systems and data development, you will play a pivotal role in enhancing the efficiency and effectiveness of our data processes.

Benefits

Health insurance
Dental insurance
Vision insurance
Life Insurance
401(k) Retirement Plan with matching
Paid Time Off
Paid Federal Holidays

Required

Must be a U.S. Citizen.
Bachelor’s degree in computer science or related field, with a minimum of seven (7) years of relevant work experience.
Active security clearance or the ability to obtain one is required.

Key Skills and Example Project Experience

Data Architecture and Design Skills:
Data modeling (conceptual, logical, and physical)
Database schema design
Understanding of different database paradigms (relational, NoSQL, graph databases, etc.)
ETL (Extract, Transform, Load) processes and tools
Experience with modern data warehousing solutions (e.g., Redshift, Snowflake, BigQuery)
Project Experience: Designing and implementing scalable data architectures that support business intelligence, analytics, and machine learning workflows.

Data Pipeline Development Skills:

Proficiency in tools like Apache Kafka, Airflow, Spark, Flink, or NiFi
Experience with cloud-based data services (AWS Glue, Google Cloud Dataflow, Azure Data Factory)
Real-time and batch data processing
Automation and monitoring of data pipelines
Project Experience: Leading the development of highly available, fault-tolerant, and scalable data pipelines, integrating multiple data sources, and ensuring data quality.

Cloud Platforms and Services Skills:

Expertise in cloud environments (AWS, GCP, Azure)
Understanding of cloud-based storage (S3, Blob Storage), databases (RDS, DynamoDB), and compute resources
Implementing cloud-native data solutions (Data Lake, Data Warehouse, Data Mesh)
Project Experience: Migrating legacy data infrastructure to the cloud or developing new data platforms using cloud services, with a focus on cost efficiency and scalability.

Big Data Technologies Skills:

Experience with big data ecosystems (Hadoop, HDFS, Hive, Spark)
Distributed computing, parallel processing, and handling petabyte-scale data
Tools for querying large datasets (Presto, Athena)
Project Experience: Building and managing big data platforms to enable large-scale analytics, often incorporating structured and unstructured data.

Database Administration and Optimization Skills:

Expertise in database technologies (SQL, NoSQL, GraphDBs)
Query optimization, indexing, and partitioning strategies Backup, replication, and disaster recovery planning

Project Experience:

Performance tuning for complex queries, implementing database replication and sharding strategies to support high availability and scalability.
Data Governance and Security Skills:
Data privacy, encryption, and compliance with regulations (GDPR, CCPA)
Implementing data governance frameworks (data lineage, cataloging, metadata management)
Role-based access control and user management for sensitive data

Project Experience: Developing and implementing data governance policies and security controls across the organization’s data assets, ensuring compliance with industry standards.

Programming and Scripting Languages
Proficiency in Python, Scala, SQL, and Java
Experience with version control (Git) and CI/CD for data engineering (Gitlab, Jenkins, CircleCI)
API design and integration (Postman)
Project Experience: Automating data workflows, building custom tools for data processing, and integrating APIs with third-party data sources.

AI/ML Pipeline Support and Analytics

Experience in supporting data scientists with feature engineering, data wrangling, and model deployment
Knowledge of ML orchestration tools (MLflow, Kubeflow)
Hands-on experience with analytics tools (e.g., Tableau, Power BI)
Project Experience: Designing architectures that support AI/ML initiatives, enabling scalable data pipelines for training models, and supporting experimentation in the production environment.

Leadership and Mentorship

Leading data engineering teams, cross-functional collaboration with data scientists, analysts, and business units
Project management (Agile, Scrum, Kanban) and stakeholder communication
Experience with mentorship and growing junior data engineers
Project Experience: Leading the technical direction for large-scale data initiatives, such as enterprise data lake implementations or the creation of a unified data platform.

Business and Domain Knowledge:

Understanding of the industry and business processes (e.g., aviation, finance, healthcare, e-commerce, or manufacturing)
Ability to translate business requirements into technical specifications
ROI calculation and cost-benefit analysis of data solutions
Project Experience: Collaborating with business units to build data solutions that drive strategic decision-making, delivering measurable business value.

Additional Skills:

DevOps/DataOps: Familiarity with infrastructure as code, containerization (Docker, Kubernetes), and automation of deployment pipelines for data infrastructure.
Version Control and CI/CD: Managing data engineering projects with versioningtools like Git and incorporating CI/CD practices for continuous integration of data workflows.

Responsibilities

The Data Engineer (DE) will ensure that backend data pipelines and operations run smooth from multiple data providers. The DE will be responsible for leading end-to-end data management activities, including but not limited to working with partners to identify fields, data linkage and integration, performing data quality checks, analysis, presenting data and documenting the process.
The DE must be able to review and understand large sets of data while being able to highlight relevant trends and patterns. The ideal candidate is a quick learner, curious, innovative, results oriented and has strong interpersonal skills.
Key responsibilities include:
Take the lead role in data transfer operations. Actively develop and maintain data pipelines and workflows that are the foundation of our polling and modeling: problem scoping, data cleaning, analysis, and testing.
Create, Index, Query, and Update SQL tables/servers.
Use Azure Databricks (Spark) and Data Factory to manage pipelines.
Run/update Python and/or JavaScript code to parse data.
Maintain data in S3 buckets and Blob storage.
Use schedulers and APIs to get near real-time data.
Work closely with partners to acquire, clean, and load new datasets.
Collaborate with and support the work of the data scientists to produce deliverables.
Develop and implement data acquisition, quality assurance and management protocols.
Develop other workflows and automate processes using Python or other scripting languages.
Create, maintain, and organize technical documentation for all data collection, cleaning, and analyses to inform both internal external users about data products and methodology.
Additional Scripting and coding to automate and monitor data management processes.
Assist with maintenance and development of internal Analytics data architecture.
Exercise independent judgement and original thinking in support of data projects.
Design, write, and disseminate innovative and visually appealing reports.

$116,000 - $126,000 a year

A salary commensurate with background and experience will be offered.

SteerBridge Strategies 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.

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