Data Engineer at Elder Research in Arlington, VA

Job description

• Elder Research Inc., a wholly owned subsidiary of MANTECH international Corporation seeks a motivated, career and customer-oriented Data Engineer to join our team in Arlington, VA. This is a hybrid position Preferably located in the Washington DC area.
• As a Data Engineer, you will support the Internal Revenue Service’s mission to combat tax fraud, identity theft, and non-compliance by designing and delivering secure, scalable, and automated data pipelines that power advanced analytics, machine learning models, and decision-support tools. You will work directly with IRS stakeholders, program managers, data scientists, and technical teams to translate complex business and compliance needs into reliable data engineering solutions.
• Your work will enable fraud detection, audit prioritization, refund review, and compliance risk analysis across large, sensitive tax and financial datasets. This role sits within an analytics-focused business unit supporting IRS enforcement, compliance, and research initiatives, partnering closely with data science and analytics teams to ensure data products are production-ready, trustworthy, and mission-aligned.

Responsibilities

• Troubleshoot and resolve complex data and system issues across cross-functional and mission-critical environments with minimal supervision
• Engineer solutions that integrate diverse data types, including transactional, financial, and textual data, to support compliance and fraud analytics
• Collaborate with data scientists and stakeholders to deploy analytics applications, dashboards, and decision-support tools
• Write, test, and refine reusable, well-documented code in Python, SQL, Java, and other languages using collaborative development practices
• Build and maintain secure, scalable data pipelines and end-to-end systems, including operation within air-gapped or restricted government environments
• Support the full engineering lifecycle, from concept and design through deployment, monitoring, and ongoing support
• Produce technical documentation and deliver briefings or presentations to technical and non-technical audiences
• Act as a technical consultant, translating business, compliance, and enforcement needs into effective data solutions

Requirements

• 2–7+ years of experience in data science, analytics, or a related technical field, with prior programming experience, preferably in Python
• Bachelor of Science degree in a relevant field such as statistics, computer science, economics, mathematics, analytics, data science, data engineering, business, or social sciences
• Design, build, and deploy robust, repeatable, and automated data pipelines using Python and SQL to transform raw data into analytics and ML-ready datasets
• Engineer data pipelines that support fraud detection, compliance analytics, and predictive risk modeling across structured and unstructured data sources in Databricks
• Develop and maintain end-to-end machine learning data workflows across on-premises and cloud environments, integrating backend systems with analytics platforms and user-facing applications
• Partner closely with data scientists, analysts, product managers, and government stakeholders to align data engineering solutions with IRS mission objectives, and translate client and stakeholder requirements into clear, actionable technical designs and implementation plans
• Modernize and optimize data and ML workflows by implementing best practices for scalability, reliability, maintainability, and security, while contributing effectively within agile, fast-paced development environments supporting iterative delivery and continuous improvement
• Demonstrate a strong willingness to learn new technologies, adapt to evolving requirements, share knowledge across teams, and travel and work on-site with clients as project needs require
• Must currently possess an IRS Public Trust clearance with Full Background Investigation
• Advanced degree (MS) in analytics, computer science, data science, mathematics, statistics, engineering, management information systems, decision science, or related fields
• Experience with version control systems (Git, SVN, Mercurial) and collaborative programming practices (pair programming, code reviews), as well as containerization and environment management (venv, conda)
• Experience with platforms and technologies such as Databricks and AWS, including prior Databricks experience in Unity Catalog, PySpark, Spark SQL, and Jobs
• Familiarity with vector, object, and document-based data storage systems, and experience implementing data engineering solutions in remote or austere environments, including use of bash and command-line tools
• Experience with business intelligence and data visualization tools (Power BI, Tableau), and understanding of the data analytics lifecycle (e.g., CRISP-DM) and how engineering supports downstream analytics and ML use case

Skills

Required

• Python
• SQL
• Java
• Databricks
• Data pipeline engineering
• Machine learning workflows
• Cloud environments
• Agile development
• Technical documentation
• Communication
• Collaboration

Preferred

• Git
• SVN
• Mercurial
• Pair programming
• Code reviews
• Containerization
• venv
• conda