Senior Data Engineer (AWS & Databricks)

Senior Data Engineer (AWS & Databricks)
Компания: GDIT
**Type of Requisition:** Pipeline **Clearance Level Must Currently Possess:** None **Clearance Level Must Be Able to Obtain:** None **Public Trust/Other Required:** BI Full 6C (T4) **Job Family:** Data Science and Data Engineering **Job Qualifications:** **Skills:** Amazon Web Services (AWS), Databricks Administration, Databricks Platform, Extract Transform & Load (ETL) Tools **Certifications:** None **Experience:** 5 + years of related experience **US Citizenship Required:** No **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 environ