Enterprise Process Engineer

Capgemini Government Solutions (CGS) LLC is seeking a highly motivated Enterprise Data Process Engineer, responsible for analyzing, documenting, and improving business and technical processes in support of government program objectives. The role involves evaluating end-to-end workflows within complex enterprise and data environments and providing recommendations related to system design, process efficiency, and the application of emerging technologies.

Responsibilities:

• Data Architecture as a Process: Deep experience in analyzing and optimizing the processes of a large-scale data ecosystem. This includes designing workflows for data publishing, discovery, and consumption in a decentralized or federated environment (e.g., Data Mesh or Data Fabric)
• Technical Process Validation: Demonstrable experience in analyzing technical deliverables against contractual requirements (SOW) and validating that the delivered system's functionality aligns with the stated business process
• System Integration & Workflow Analysis: Strong understanding of how disparate systems and APIs connect, with the ability to model and analyze the end-to-end data flow to identify inefficiencies and risks
• Enterprise System Engineering: Proven ability to provide strategic recommendations on technology choices by analyzing their impact on long-term business processes, cost, and efficiency
• Familiarity with the workflows and processes of data analytics and data science teams
• Working knowledge of AI/ML concepts and their application to business process automation
• Strong communication and presentation skills, with the ability to translate complex data into actionable insights. Excellent problem-solving and critical-thinking abilities
• Ability to collaborate with cross-functional teams and manage multiple stakeholders, including government agencies

Requirements:

• U.S. Citizenship is required
• Eligible to obtain and maintain a Government Security Clearance
• Master's degree or higher in data science, statistics, computer science, economics, mathematics, information systems, or similar field preferred or additional equivalent experience
• Minimum of 8 years of progressive professional experience (relevant advanced degrees may substitute equivalent number of years) with data science, AI/ML, or deep learning delivery responsibilities such as: Managing teams to deliver work products that comply with quality, time, and technical targets, Coordinating and influencing stakeholders, managing communications, and managing client expectations, Designing and developing data models and algorithms for multi-objective optimization and decision making, Building and deploying predictive and prescriptive analytics, Conducting hypothesis testing, statistical and probability analyses, Applying appropriate methods to describe statistical relationships between variables, Performing multiple correspondence analysis (MCA), principal component analysis (PCA), and association rule mining