Senior Data Engineer

Senior Data Engineer

Seize your opportunity to make a personal impact supporting the Case Management Modernization (CMM) Program.  The CMM program is an initiative to support the Administrative Office of the US Courts (AO) 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 work as part of the CMM Data Modernization and Governance team responsible for delivering an integrated data governance, engineering, data platform, reporting, analytics, and Artificial Intelligence (AI)/Machine Learning (ML) capabilities that support operational decision-making and fulfill AO's data and analytics objectives in support of the CMM program.

The successful candidate is 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.

The Senior Data Engineer will execute the following responsibilities:

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., Snowflake, Databricks, or AWS Redshift)
• 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.

QUALIFICATIONS

• MA/MS degree with 5+ years or BS/BA degree with 7+ years of general experience in information systems and 5+ years of specialized experience.
• Experience may be considered in lieu of degree as follows: HS (16+ years), AA/AS (14+ years), BA/BS (12+ years), Doctorate Degree/Ph.D. (9+ years).
• Experience in data engineering and design data architecture.
• Experience and understanding of best practices regarding system security measures.
• Experience with building and migration 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 with AWS data and compute services.
• Experience with data orchestration tools.
• Knowledge of cloud messaging and storage services.
• Proven track record in software and data engineering roles.
• Hands-on experience building enterprise-scale data pipelines.
• Strong proficiency with SQL, Python and data transformation techniques.
• Experience developing in cloud-based data platforms.
• Familiarity with Agile/Scrum delivery environments.
• Experience working in regulated or compliance-driven environments.
• Experience supporting data platforms or analytics programs.
• Hands-on experience with Data Platforms.
• Proficiency with ETL/ELT frameworks.
• Experience with streaming or near–real-time data ingestion.
• Familiarity with data governance, metadata, and classification standards.
• Experience mentoring junior data engineers.
   

COMMUNICATION & ORGANIZATIONAL

• Excellent presentation and communication (oral and written) skills.
• Consultant mindset with the ability to work with high level customer stakeholders and build excellent customer relationships.
• Experience identifying and applying industry tools, solutions, methods best practices, and emerging technologies.
• 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.

CERTIFICATIONS (Preferred)

• Certified Data Management Professional (CDMP)
• Snowflake SnowPro Core
• Databricks Certified Data Professional
• AWS Certified Data Analytics - Specialty
• AWS Certified Solutions Architect - Professional
• AWS Certified Data Engineer