Senior Business Analyst Data Analytics

At TE, you will unleash your potential working with people from diverse backgrounds and industries to create a safer, sustainable and more connected world. Job Overview Specializes in data architecture for reporting services, and designing expertise in data warehouses, data marts, and business intelligence (BI) enterprise reporting. Identifies ways to increase the use of BI within TE, designing end-to-end BI solutions that provide insights and information for key decision-makers. Identifies and interprets trends and patterns in datasets to locate influences. Constructs forecasts, recommendations and strategic/tactical plans based on business data and market knowledge. Creates specifications for reports and analysis based on business needs and required or available data elements. May provide consultation to users and lead cross-functional teams to address business issues. Role Overview Reporting directly to the Energy CIO (with a dotted line to the IS Analytics Leader), you will collaborate with TEIS technical teams across three regions. You will partner with business functions to embed AI and automation across operations, sales, marketing, and digital teams. Why you should join We are seeking a strategic and hands‑on Business Analyst to lead data, analytics, and AI initiatives within the Energy Business Unit. This role will drive data quality, advanced analytics, and AI adoption to enable business transformation, accelerate enterprise standards, and modernize legacy systems. You will act as a bridge between business opportunity, digital capability, and advanced analytics, ensuring every initiative delivers tangible value. Key Responsibilities AI Strategy & Product Delivery Lead end-to-end design and delivery of AI-powered tools and automation solutions across business functions. Identify and prioritize high-value AI, advanced analytics, and data science use cases aligned with strategic priorities. Build ROI-based business cases and own success metrics from prototype through scale. Business Engagement & Demand Shaping Partner with business leaders to identify analytics, data science, and AI opportunities. Shape and prioritize data-driven use cases aligned with business goals and enterprise solutions. Establish a demand management framework to connect business needs with data capabilities. Data Platform Adoption & Modernization Drive adoption of scalable data products and the One Data Platform. Advise on data integration, self-service analytics, and advanced AI/ML capabilities. Lead retirement of legacy platforms and migration to modern solutions. Define KPIs for system decommissioning and cost optimization. Data & AI Literacy, Enablement, and Culture Building Execute training programs and “AI Quick Start” initiatives to enable self-service analytics and AI adoption. Foster a data-driven culture through awareness, best practices, and success stories. Build and sustain an AI community of practice to share tools and lessons learned. Data Readiness & Governance Partner with Data & Analytics teams to ensure priority AI use cases have the required data access and quality. Identify and resolve critical data gaps, recommend improvements, and ensure alignment with governance and security standards. Leverage enterprise data platforms (Salesforce, SAP, Databricks, etc.) for active AI projects. Responsible AI & Measurement Establish and communicate clear principles for responsible AI use, ensuring ethical, transparent, and compliant application. Develop KPIs and dashboards to track AI adoption, impact, and ROI. Measure business value delivered through AI (revenue growth, cost avoidance, efficiency gains). Continuous Innovation & Partnerships Stay current on emerging AI tools and technologies. Evaluate partnerships with vendors, startups, and enterprise teams to accelerate deployment. Encourage experimentation through safe pilot environments and scale successful ideas. Assess the suitability and potential impact of emerging technologies, including agentic AI, large language models (LLMs), and cognitive automation. Qualifications Required Bachelor’s degree in Computer Science, Engineering, Data Science, or related field; advanced degree (MBA, MS, or equivalent) preferred. 10+ years in data and analytics leadership, digital product management, or applied AI roles within complex organizations. Proven track record delivering measurable business outcomes through AI, automation, or digital transformation. Hands‑on experience with LLMs, prompt engineering, Python scripting, or workflow automation. Strong understanding of data systems (Databricks, Snowflake, Azure Synapse, SAP, Salesforce) and governance principles. Exceptional ability to translate complex technical concepts into business‑relevant narratives and use cases. Strong communication and influence skills; able to inspire adoption and align senior stakeholders. Demonstrated success in driving organizational change and data literacy. Preferred Experience in manufacturing, supply chain, sales & ops planning, or shop floor data. Knowledge of modern cloud architectures (Databricks, Snowflake, Azure, AWS, GCP). Strong understanding of AI ethics, data privacy, and regulatory frameworks. Effective collaboration across technical and business teams. Core Competencies Values: Integrity, Accountability, Inclusion, Innovation, Teamwork Skills: Business acumen, change management, strategic thinking, leadership, and collaboration. Success Metrics Business impact: Value created via AI-enabled use cases (revenue growth, cost savings, efficiency). Adoption: Percentage of teams using AI tools and automation. Enablement: Number of employees completing AI literacy programs. Scalability: Reuse rate of AI models and tools across functions. Cultural change: Demonstrated AI-first mindset and proactive experimentation. Join our team and play a pivotal role in transforming how the Energy Business Unit leverages data, analytics, and AI to drive growth, efficiency, and innovation. If you’re passionate about building innovative solutions and shaping the future of work, we’d love to hear from you. #J-18808-Ljbffr