Data Engineer

• Design, build, and maintain scalable data pipelines for structured and unstructured data
• Develop, optimize, and manage ETL/ELT processes and data ingestion platforms, including cloud-based solutions
• Build and maintain data warehouse environments and support data modeling efforts
• Ensure data quality, integrity, security, and compliance across all data systems
• Collaborate with data scientists, data architects, and stakeholders to deliver data solutions
• Support and operationalize machine learning models and analytics workflows
• Develop and maintain APIs for data access and integration
• Monitor and troubleshoot data infrastructure to ensure performance and reliability
• Implement automation using metadata management and modern data engineering practices
• Provide ad hoc data analysis and support self-service data access for stakeholders
• Design and maintain reporting and dashboarding infrastructure
• Promote best practices in data engineering, governance, and data lifecycle management
• Support data tagging, metadata management, and enterprise data governance initiatives
• Assist in developing data-related policies, documentation, and system requirements
• Research and recommend improvements to modernize data architecture, including cloud adoption

• Bachelor?s or Master?s degree in Computer Science, Data Science, Information Systems, or a related quantitative field
• Equivalent work experience may be considered in lieu of a degree
• Minimum of ten (10) years of IT experience, including at least six (6) years in data engineering or related disciplines
• Strong experience designing and optimizing data pipelines and architectures
• Expertise in ETL/ELT processes, data integration, and data warehousing concepts
• Proficiency in SQL and programming languages such as Python, Java, R, or Scala
• Experience working with large, complex, and heterogeneous datasets
• Strong understanding of data modeling, schema design, and metadata management
• Experience with cloud platforms (AWS, Azure, GCP) and hybrid environments
• Knowledge of DevOps/DataOps practices, including CI/CD for data pipelines
• Familiarity with message queuing, stream processing, and real-time data integration technologies
• Strong analytical, problem-solving, and communication skills

Core Competencies:

• Ability to design and optimize scalable, high-performance data systems
• Strong collaboration skills across technical and business teams
• Expertise in data governance, data quality, and data security practices
• Ability to translate business requirements into technical data solutions
• Adaptability in working with evolving technologies and complex environments, * Experience supporting Department of Defense (DoD), Department of Navy (DoN), or law enforcement environments
• Familiarity with federal data governance and compliance requirements
• Experience with data visualization tools such as Tableau, Power BI, or Qlik
• Cloud certifications (AWS, Azure, or GCP)
• Experience with NoSQL, Hadoop, or big data ecosystems
• Experience collaborating with data science teams to operationalize machine learning models