Senior Data Engineer

General Dynamics Information Technology (GDIT) is a global technology and professional services company that delivers consulting, technology and mission services to every major agency across the U.S. government. They are seeking a Senior Data Engineer to provide advanced analytical, machine learning, and data engineering support, focusing on developing and deploying machine learning models and data pipelines to drive data-informed decision-making.

Responsibilities:

• Design, develop, and deploy machine learning models for classification, regression, time series forecasting, and natural language processing applications to solve complex business problems
• Build and optimize automated, scalable ETL/ELT pipelines using Python, SQL, and cloud-based tools to integrate, transform, and validate structured and unstructured data from diverse sources
• Develop and maintain production ML systems including model deployment, monitoring, versioning, and performance tracking in collaboration with AI/ML infrastructure teams
• Design, develop, and deploy interactive dashboards and data visualizations using Tableau, Power BI, or similar platforms to deliver actionable insights to technical and executive stakeholders
• Perform end-to-end model development including exploratory data analysis, feature engineering, hyperparameter tuning, model validation, and documentation
• Develop and maintain data pipelines and workflows using tools such as AWS services, Databricks, and GitLab CI/CD to support analytics and ML operations
• Conduct data mining, cleaning, and manipulation using SQL, Python (Pandas, NumPy), or R to deliver statistical analyses, visualizations, and predictive insights
• Translate complex business requirements into technical solutions, data models, and analytical frameworks that align with long-term technology strategy
• Provide technical mentorship to team members on advanced analytics techniques, Python scripting, ML best practices, and workflow automation
• Create comprehensive documentation including data dictionaries, metadata, technical specifications, and presentations for diverse audiences
• Respond to urgent and ad-hoc data requests, compile reports for leadership, and coordinate collaborative research and analysis projects
• Partner with cross-functional teams including data engineers, software developers, and federal stakeholders to ensure production readiness and scalability of data solutions

Requirements:

• 5 + years of related experience
• BS/BA degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field
• At least 5 years of experience in data science, machine learning, or advanced analytics; 3 years of experience with a master's degree
• Experience with CI/CD pipelines (GitLab CI/CD) for data workflows
• Strong proficiency in Python and SQL for data manipulation, analysis, and pipeline development
• Experience with ETL/ELT pipeline development and data engineering best practices
• Demonstrated knowledge of data visualization platforms (Tableau, Power BI) and ability to translate technical insights into executive-level dashboards
• Experience with cloud platforms and modern data infrastructure
• Knowledge of statistical analysis and modeling techniques
• Understanding of relational and non-relational databases (Oracle SQL, PostgreSQL, etc.)
• Strong version control and collaboration skills using Git (GitHub, GitLab)
• Exceptional analytical skills with strong attention to detail
• Strong written and verbal communication skills with ability to present complex findings to non-technical stakeholders
• Must be able to work both independently and as part of a collaborative team in a fast-paced, agile environment
• Familiarity with ML orchestration tools (e.g. Kubeflow, ML Flow, Air Flow, Sage Maker, or similar)
• Experience with MLOps practices including model monitoring, versioning, and production deployment
• Experience with data orchestration and workflow automation tools
• Experience working with federal government data systems and compliance requirements
• Background in Agile/Scrum methodologies and project management tools (Jira)
• Experience mentoring junior data professionals and establishing analytics best practices