Senior data engineer (aws & databricks)

Telecommunting: Remote

Travel Requirement: Less than 10%

Clearance Level Must Be Able to Possess: None

Clearance Level Must Be Able to Obtain: None

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

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.

U.S. Person status is required. This includes U.S. citizens, U.S. nationals, lawful permanent residents (Green Card holders), and certain protected individuals as defined by U.S. regulations. Visa sponsorship is not available for this role.

This role will require you to obtain and maintain a 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.

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