Senior Data Analytics Engineer

• Partner with business stakeholders to define problems, gather requirements, and deliver data-driven solutions
• Analyze large, complex datasets (structured and unstructured) to uncover trends and insights
• Build, validate, and deploy predictive models and machine learning solutions
• Translate findings into clear, compelling narratives for both technical and non-technical audiences
• Develop dashboards, visualizations, and reporting tools to support decision-making
• Collaborate cross-functionally with data engineers, analysts, architects, and business teams
• Contribute to data quality improvements, root cause analysis, and issue resolution
• Lead or support projects across data science, analytics, and business intelligence initiatives
• Mentor team members and promote best practices across analytics and data science
• Support the evolution of a data-driven center of excellence culture

Data Analysis, United States Citizen, Data Science, Problem Solving Skills, Business Skills, Storytelling, Communication Skills, Requirements Management, Data Sets, Analysis Skills, The ideal candidate combines strong technical expertise with business acumen, communication skills, and the ability to influence decisions through data storytelling., * Strong experience working directly with business partners (not just technical teams)

• Ability to own the full lifecycle: requirements solution communication business impact
• Proven ability to tell a story with data and influence decision-making
• Excellent communication and interpersonal skills
• Experience in supply chain, operations, or related business functions
• Comfortable working in collaborative, highly visible environments, * Programming: Python, R (additional languages such as C are a plus)
• Data & ML: Machine learning, statistical modeling, data analysis
• Tools: Azure Databricks, Spark, Power BI, Excel (advanced functions/pivot tables)

• Experience working with large-scale datasets and distributed computing environments, * Industry experience in manufacturing, automotive, industrial, engineering, or similar environments (Healthcare, retail, biotech also considered; heavy financial services backgrounds less aligned)

• Experience with:
• Power Platform tools
• Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)

• Front-end data apps (Flask, Gradio, etc.), * Bachelor’s degree + 5+ years of relevant experience OR

• Master’s degree + 3+ years of relevant experience

• Demonstrates clear business impact from data science work
• Builds solutions that are adopted and used by stakeholders
• Communicates insights in a way that drives action
• Operates as a trusted partner to the business, not just a technical resource