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Added 6 mins ago
Lead Hardware Engineer | Electrical/Mechanical (ADAS) | Remote
Cherry Bekaert
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Our client is seeking a Lead Hardware Engineer to build the next generation of automotive diagnostic and ADAS calibration equipment. This is a hands-on, highly visible role for a builder…
Added 6 mins ago
Lead Hardware Engineer | Electrical/Mechanical (ADAS) | Remote
Cherry Bekaert
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Our client is seeking a Lead Hardware Engineer to build the next generation of automotive diagnostic and ADAS calibration equipment. This is a hands-on, highly visible role for a builder…
Added 6 mins ago
Lead Hardware Engineer | Electrical/Mechanical (ADAS) | Remote
Cherry Bekaert
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Added 6 mins ago
Lead Hardware Engineer | Electrical/Mechanical (ADAS) | Remote
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Lead Hardware Engineer | Electrical/Mechanical (ADAS) | Remote
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Lead Hardware Engineer | Electrical/Mechanical (ADAS) | Remote
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Lead Hardware Engineer | Electrical/Mechanical (ADAS) | Remote
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Lead Hardware Engineer | Electrical/Mechanical (ADAS) | Remote
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Added 6 mins ago
Lead Hardware Engineer | Electrical/Mechanical (ADAS) | Remote
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Added 6 mins ago
Lead Hardware Engineer | Electrical/Mechanical (ADAS) | Remote
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General Dynamics Information Technology

Senior Data Engineer (AWS & Databricks)

Fairfax, VA, United States

The likely salary range for this position is $111,155 - $150,385.

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Job details

Pay: The likely salary range for this position is $111,155 - $150,385.
Education: Bachelor’s degree
Experience: Required: Bachelor’s degree in Data Science or closely-related discipline and 5+ years of specialized experience with AWS Cloud & Databricks
Posting language: English
Posted: Nov 6, 2026

Original job description

Req ID: RQ231758

Type of Requisition: Regular

Clearance Level Must Be Able to Obtain: None

Public Trust/Other Required: BI Full 6C (T4)

Job Family: Data Science and Data Engineering

Skills:

Amazon Web Services (AWS),Databricks Administration,Databricks Platform,Extract Transform & Load (ETL) Tools

Experience:

5 + years of related experience

Job Description:

Seize your opportunity to make a personal impact supporting the Case Management Modernization (CMM) Program , an initiative to support the Administrative Office of the US Courts (AOUSC) in developing a modern, cloud-based solution to support all 204+ federal courts across the United States.

GDIT is your place to make meaningful contributions to challenging projects and grow a rewarding career. The Senior Data Engineer will leverage their expertise with AWS Cloud and the Databricks platform to help the CMM Data Modernization and Governance Team deliver integrated data governance, engineering, data platform, reporting, analytics, and AI/ML capabilities that support operational decision-making and fulfill the AOUSC’s data and analytics objectives in support of the CMM Program .

The Senior Data Engineer will be responsible for designing, building, testing, and maintaining scalable data engineering components and platform services that power the CMM Program . This role delivers high-quality, secure, and performant data pipelines, transformations, ETL/ELT delivery, data management solutions, and system integrations aligned with federal standards and CMM objectives for modernization, analytics, and operational excellence. The Senior Data Engineer partners closely with the Data Architecture, Data Governance, and Migration teams to ensure engineering work is consistent, auditable, and aligned with CMM's cloud-based CI/CD standards.

If you're interested in engineering mission-critical data solutions while growing your career with a company that always puts our people at the forefront of everything we do, then we'd love to hear from you!

MEANINGFUL WORK AND PERSONAL IMPACT

As a Senior Data Engineer , the work you’ll do at GDIT will be impactful to the mission of the AOUSC . You will play a crucial role in:

Data Platform & Architecture

Develop and implement a scalable, secure, cloud-based data platform supporting operational data, reporting, and analytics delivering cloud-based architecture (data lake, lakehouse, or data warehouse).
Ensure alignment with federal security requirements, judiciary architecture standards, data governance policies, and application modernization initiatives
Engineer multi-tenant, cloud-based environments supporting hybrid/on‑premises systems, enabling SQL, NoSQL, IaaS, PaaS, distributed SQL, multi-modal, and event-driven/streaming databases.
Produce and maintain dimensional data models that form the basis for the data marts to satisfy the requirements of the data products
Develop and maintain downstream data marts and / or consumable data and their corresponding ETL/ELT processes (on a near real-time basis or overnight batch depending on the individual uses case requirements) and their associated reports and dashboards
Develop and maintain comprehensive documentation including the STTMs, data models (logical and physical), design documents, testing documents and other related documents
Develop, deploy and maintain the data presentation and data reports for each of the data products using visualization or presentation tool(s) selected by the customer
Support development of the Data and Technology Enabler Roadmap across data engineering, reporting/analytics, and AI/ML use cases

Data Engineering & Integration

Design and develop data ingestion, ETL/ELT pipelines for integrating data from multiple enterprise sources, and transformation logic for near-real-time and batch workloads
Implement robust, reusable data services supporting analytics, reporting, and downstream data marts and / or gold layers
Collaborate with architects to implement logical and physical data models in cloud-based platforms (e.g., Databricks )
Develop and maintain high-quality, testable code using secure coding standards and best practices
Support the operationalization CMM Data Classification Standards, including workshops, security controls, metadata requirements, and integration into system design, procurement, and training
Configure metadata structures, workflows, automation, and security settings; develop ingestion processes and attribute definitions for catalog entries
Create training, job aids, and communications to support user adoption
Integrate data pipelines with cloud services, messaging, and storage components
Implement data quality checks, validations, and error-handling mechanisms
Optimize pipeline performance, scalability, and cost efficiency.
Support CI/CD-enabled deployments, including automated testing and promotion across environments
Participate in code reviews, design reviews, and sprint ceremonies.
Support incident resolution and root cause analysis for data pipeline failures
Produce and maintain technical documentation, runbooks, and workflows
Ensure deliverables meet federal security, governance, and audit requirements
Operates within an Agile federal delivery environment across multiple scrum teams
Collaborates closely with architects, DBAs, business analysts, and QA personnel
Accountable for code quality, performance, and delivery timelines.
Expected to maintain audit-ready documentation and technical artifacts

Data Migration & Archiving

Partners closely with the Data Architecture, Data Governance, and Migration teams to execute the data migration, archival, and disaster recovery (DR) strategy
Deliver migration documentation for scripts, transformations, and validation results
Support the Failover Testing and DR drills engineering activities
Implement operational databases supporting data migration, archival, DR, document storage, indexing services, schemas, and secure data APIs using IaC for provisioning and configuration

WHAT YOU’LL NEED TO SUCCEED

Bring your expertise and drive for innovation to GDIT. The Senior Data Engineer must have:

Education & Experience:

Required: Bachelor’s degree in Data Science or closely-related discipline and 5+ years of specialized experience with AWS Cloud & Databricks
Preferred: Bachelor’s degree and 7+ years of specialized experience with AWS Cloud & Databricks -or- Master’s degree and 5+ years specialized experience with AWS Cloud & Databricks

Required Skills:

Deep, hands-on experience with core AWS data storage, compute, and serverless tools
Deep, hands-on experience with Databricks , Apache Spark, and Delta Lake
Advanced proficiency in Python, PySpark, SQL, and data transformation techniques
Proficiency with ETL/ELT frameworks
Familiarity with version control (Git), containerization, CI/CD, and data governance frameworks (e.g., Unity Catalog)
Hands-on experience building enterprise-scale data pipelines
Experience with streaming or near–real-time data ingestion
Familiarity with data governance, metadata, and classification standards
Experience and understanding of system security best practices
Experience with building and migrating software and IT services to align to strategic business needs and goals
Experience in conducting research for advanced technologies to determine how IT can support business needs by leveraging software, hardware, or infrastructure
Experience identifying and applying industry tools, solutions, methods best practices, and emerging technologies
Familiarity with Agile/Scrum delivery environments
Experience working in regulated or compliance-driven environments
Excellent presentation and communication skills
Consultant mindset with the ability to work with high level customer stakeholders and build excellent customer relationships
Strong analytical skills and problem-solving skills with the ability to formulate and communicate recommendations for improvement
Demonstrated ability to work effectively, independently, and as part of a team
Experience mentoring junior data engineers

PREFERRED CERTIFICATIONS:

One or more of the following certifications is preferred but not required :

Databricks Certified Data Professional
AWS Certified Data Analytics - Specialty
AWS Certified Solutions Architect - Professional
AWS Certified Data Engineer

SECURITY CLEARANCE LEVEL:

Public Trust: This role will require you to pass a background check to obtain a position of Public Trust and will require you to provide onsite fingerprinting at a designated facility. This investigation may review personal and criminal behavior, financial conduct, foreign influence, as well as other adjudications.
Must be a US Person (Green Card Holder, US Permanent Resident Alien, Refugee, Asylee, or US Citizen).

LOCATION:

Remote

GDIT IS YOUR PLACE

At GDIT, the mission is our purpose, and our people are at the center of everything we do.

Growth: AI-powered career tool that identifies career steps and learning opportunities
Support: An internal mobility team focused on helping you achieve your career goals
Rewards: Comprehensive benefits and wellness packages, 401K with company match, and competitive pay and paid time off
Community: Award-winning culture of innovation and a military-friendly workplace

OWN YOUR OPPORTUNITY

Explore a career in data science and engineering at GDIT and you’ll find endless opportunities to grow alongside colleagues who share your determination for solving complex data challenges.

#GDITLA

The likely salary range for this position is $111,155 - $150,385. This is not, however, a guarantee of compensation or salary. Rather, salary will be set based on experience, geographic location and possibly contractual requirements and could fall outside of this range.

Total Rewards at GDIT:

Our benefits package for all US-based employees includes a variety of medical plan options, some with Health Savings Accounts, dental plan options, a vision plan, and a 401(k) plan offering the ability to contribute both pre and post-tax dollars up to the IRS annual limits and receive a company match. To encourage work/life balance, GDIT offers employees full flex work weeks where possible and a variety of paid time off plans, including vacation, sick and personal time, holidays, paid parental, military, bereavement and jury duty leave. GDIT typically provides new employees with 15 days of paid leave per calendar year to be used for vacations, personal business, and illness and an additional 10 paid holidays per year. Paid leave and paid holidays are prorated based on the employee’s date of hire. The GDIT Paid Family Leave program provides a total of up to 160 hours of paid leave in a rolling 12 month period for eligible employees. To ensure our employees are able to protect their income, other offerings such as short and long-term disability benefits, life, accidental death and dismemberment, personal accident, critical illness and business travel and accident insurance are provided or available. We regularly review our Total Rewards package to ensure our offerings are competitive and reflect what our employees have told us they value most.

Our Identity Verification Process:

As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during virtual interviews. We reserve the right to take your picture to verify your identity and prevent fraud. By proceeding, you authorize the collection, processing, and use of your biometric data for identity verification and security purposes.

About Our Work:

We are GDIT. A global technology and professional services company that delivers technology solutions and mission services to every major agency across the U.S. government, defense and intelligence community. Our 26,000 experts extract the power of technology to create immediate value and deliver solutions at the edge of innovation. We operate across 50+ countries worldwide, offering leading mission-ready capabilities in AI, cloud, cyber and software development.

Join our Talent Community to stay up to date on our career opportunities and events at https://gdit.com/tc.

Equal Opportunity Employer / Individuals with Disabilities / Protected Veterans

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More about this job

Skills

AWS
Databricks
Data engineering
Data extraction, transformation and loading tools
Case management
Reporting
ML
Decision making
Data management
CI/CD
IMPACT
Data warehouse
Security regulations
Architecture regulations
SQL
NoSQL
Data models
Documentation
Procurement
Statistical quality control
Test automation
Root cause analysis
Implement ICT recovery system
Operational databases
Infrastructure as code
Data storage
Apache Spark
Python
PySpark
Git
Unity
Research
Agile
Scrum
Regulatory compliance
Communication skills
Customer relations
Analytical skills
Problem solving
Coaching

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