Job Title: Data Engineer/Data Analytics Detailed Job Description: We are seeking a highly analytical and forward-thinking Capabilities Lead for Data Science to support initiatives that enhance our product development lifecycle through process improvement, systems engineering, and enterprise architecture. This role is pivotal in accelerating the definition, measurement, analysis, design, and verification of innovative products by aligning technical systems with business goals and optimizing cross-functional workflows. Key Responsibilities: Process Improvement & Optimization - Identify, analyze, and improve existing engineering and R&D processes to enhance efficiency, quality, and speed. Develop and implement metrics and KPIs to measure process performance and drive continuous improvement. Facilitate root cause analysis and corrective action planning. Systems Engineering - Lead the development and management of system requirements, architectures, and interfaces across the product lifecycle. Support trade studies, risk assessments, and design verification activities. Ensure traceability from stakeholder needs through system validation. Enterprise Architecture - Design and maintain enterprise-level architecture frameworks that support scalable and sustainable product development. Align IT systems, tools, and data flows with engineering and business strategies. Collaborate with cross-functional teams to ensure architectural consistency and integration. Accelerating R&D - Champion the use of model-based systems engineering (MBSE), digital twins, and simulation tools to reduce development cycles. Integrate systems thinking into early-stage research and concept development. Support agile and lean product development methodologies. Communicate project milestones and outcomes to key business stakeholders. Qualifications: Bachelor’s or Master’s degree in Systems Engineering, Industrial Engineering, Computer Science, or a related field. 3+ years of experience in systems engineering, process improvement, or enterprise architecture roles. Familiarity with Six Sigma, Lean, or other process improvement methodologies. Software: Experience with general MS applications, Github, Azure DevOps. Background in data analytics or digital engineering. Excellent analytical, communication, and stakeholder engagement skills. Preferred Qualifications: Strong knowledge of systems engineering standards (e.g., INCOSE, ISO/IEC 15288). Experience with tools such as SysML, Enterprise Architect, DOORS, or similar. Certification in Systems Engineering (e.g., CSEP), Lean Six Sigma, or TOGAF. Software: Familiar with programming languages such as Python, SQL. Experience with tools such as DataBricks, Google BigQuery, AWS, ESRI or other GIS tools. Experience in R&D-heavy industries such as aerospace, defense, medical devices, or advanced manufacturing.