Lead Data Engineer
GDIT (General Dynamics IT) · Remote · United States · 1d ago
Type of Requisition:
PipelineClearance Level Must Currently Possess:
NoneClearance Level Must Be Able to Obtain:
NonePublic Trust/Other Required:
NoneJob Family:
Data Science and Data EngineeringJob Qualifications:
Skills:
Data Analysis, Data Analytics, Data Lake, Data Warehousing (DW)Certifications:
NoneExperience:
7 + years of related experienceUS Citizenship Required:
NoJob Description:
Lead 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 Lead 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 will serve as lead 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 Lead 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 Lead 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.
- Design and implement auditable data integration patterns across Judiciary systems and external platforms, including the legacy CM/ECF system during the coexistence period, with pipelines integrated into Government-provided CI/CD processes.
- Implement and maintain data quality controls, validation rules, and governance-aligned data structures, coordinating with the Data Quality/Validation Engineer to sustain required accuracy and field-completeness thresholds on an ongoing basis.
- Drive continuous database and query performance monitoring and optimization, including automated performance tuning, query optimization, and indexing strategies.
- Coordinate with the Cloud Data Architect/Data Modeler to ensure engineering implementation stays aligned with the Data Architecture Blueprint and evolving data models.
- Document data platform architecture, integrations, data quality metrics, and service statistics, updating this documentation each Program Increment (PI).
- Partner with DevSecOps/CI-CD engineering to ensure data pipelines are built, tested, and deployed through Government-provided CI/CD tooling.
- Escalate and help resolve technical risks, defects, and dependencies affecting data engineering delivery across the CMM program.
- 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.
- Lead the implementation and ongoing maintenance of data management solutions, including operational databases, document storage services, data models, schemas, and data access APIs.
- Provide technical direction and day-to-day oversight to the Data Engineers (ETL/ELT Pipelines) team, reviewing designs and ensuring consistent engineering standards across pipelines.
- Implement Infrastructure as Code (IaC) for database provisioning, configuration, and management to ensure consistency, repeatability, and auditability.
- 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.
- 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.
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.
QUALIFICATIONS
- MA/MS degree with 7+ years or BS/BA degree with 9+ years of general experience in information systems and 7+ 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 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.
- 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.
- Hands-on experience with data platforms, data analytics, and AI/ML solutions.
- Proficiency with ETL/ELT frameworks.
- Experience with streaming or near-real-time data ingestion.
- Familiarity with data governance, metadata, and classification standards.
- Experience in leading and mentoring 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
Scheduled Weekly Hours:
40Travel Required:
NoneTelecommuting Options:
RemoteWork Location:
Any Location / RemoteAdditional Work Locations:
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 atEqual Opportunity Employer / Individuals with Disabilities / Protected Veterans