The Senior Data Engineer will lead the development, management, and optimization of Extract, Transform, Load (ETL) pipelines and data product delivery within the CJIS Division’s Data Mesh architecture. This role ensures data integrity, governance, accessibility, and interoperability across enterprise systems, collaborating with data domain teams to deliver scalable, secure, and high-quality data solutions. The Senior Data Engineer will operate within a SAFe Agile framework, driving data modernization initiatives and fostering organizational adoption of data mesh principles.

Responsibilities: 

• Lead the design, development, and maintenance of scalable ETL pipelines using AWS services (e.g., S3, Redshift, Glue, Lake Formation, Lambda) to support data domain requirements and self-service analytics. 
• Design and deploy domain-specific data products, ensuring adherence to organizational standards for schema design, data transformations, and storage solutions. 
• Implement and enforce data governance practices, including data privacy, access controls, lineage, and metadata management, to maintain data integrity across distributed sources. 
• Manage and enhance a data catalog to support data discoverability, lineage tracking, and usage transparency across domains. 
• Support the operation, maintenance, and reliability of enterprise Data Mesh software, ensuring high availability and performance. 
• Participate in SAFe Agile ceremonies (Program Increment Planning, Sprint Planning, Daily Standups, Sprint Reviews, Retrospectives) to align development with strategic objectives. 
• Collaborate with Product Owners, Product Managers, and data domain teams to refine and prioritize the product backlog, ensuring alignment with enterprise data strategies. 
• Lead training initiatives for data stewards and users on data mesh principles, governance practices, and self-service analytics tools to drive cultural adoption. 
• Document work in Jira (Epics, Features, User Stories) and Confluence, maintaining detailed backlogs and ensuring transparency in progress tracking. 
• Utilize data governance tools to automate workflows and uphold data integrity across distributed data sources. 
• Apply cloud security best practices, including data encryption, access controls, and compliance with CJIS security standards, to protect sensitive data assets. 
• Provide team-specific training as needed to enhance data engineering capabilities.

Required Skills:

• 7+ years of experience in data engineering, with a focus on cloud-based data infrastructure and ETL pipeline development. 
• Advanced expertise in AWS data services, including S3, Redshift, Glue, Lake Formation, and Lambda, for building scalable data solutions. 
• Strong understanding of Data Mesh architecture and decentralized data management principles. 
• Comprehensive knowledge of data governance, including data privacy, access controls, lineage, and metadata management, with experience using governance tools. 
• Proficiency in programming and scripting languages (e.g., Python, Java, SQL) for ETL development, automation, and data processing. 
• Experience with data catalog tools to enhance discoverability and manage data assets across domains. 
• Proven experience in SAFe Agile environments, using Scrum, Kanban, Jira, and Confluence for work management, backlog prioritization, and documentation. 
• Strong collaboration skills to work effectively with cross-functional data domain teams and stakeholders. 
• Ability to lead training on data mesh principles, governance, and analytics tools for technical and non-technical audiences. 
• Knowledge of cloud security practices, including data encryption and compliance with federal security standards.

Preferred Qualifications:

• Experience with containerization technologies (e.g., Docker, Kubernetes, ECS) for scalable data processing. 
• Familiarity with RESTful API development for data integration and interoperability. 
• Experience with CI/CD pipelines (e.g., Bamboo, Jenkins) and Infrastructure as Code (IaC) tools (e.g., AWS CloudFormation, Ansible). 
• Knowledge of monitoring tools (e.g., AWS CloudWatch, CloudTrail, Splunk) for data infrastructure performance and troubleshooting. 
• Bachelor’s degree in Computer Science, Information Technology, or a related field. 
• Active Secret clearance 

Work Environment:

• Primarily remote, with occasional on-site requirements at the CJIS facility in Clarksburg, WV, for equipment pickup or meetings. 
• Core hours: 9:00 AM–4:00 PM ET, with potential weekend/non-business hours for maintenance and on-call support (response within one hour).