Manager of Data Analytics & Data Science

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 TE Connectivity is a global technology leader that designs and manufactures connectivity and sensor solutions, serving industries that are transforming the future. The Channel Business Unit (CBU) manages TE’s global distribution network and plays a critical role in driving growth, enhancing customer experience, and enabling commercial excellence across 300+ distributor partners worldwide. Channel BU brings together Sales Enablement, Marketing, Pricing, Customer Service, Digital, and PMO functions to accelerate revenue, deliver digitally enabled experiences, and achieve above-market growth.

Role Definition We are seeking an experienced and hands-on Data Analytics & Data Science Delivery Manager to lead and grow our India-based analytics team supporting the Channel Business Unit. This role is accountable for end-to-end delivery across three critical pillars: Channel Data Management, Analytics Products (dashboards, self-service BI, reporting), and AI / Data Science Products (predictive models, NLP, machine learning solutions). The ideal candidate combines strong people leadership with deep technical fluency, someone who can manage a team of 8–12 BI developers, analytics engineers, and data scientists while also rolling up their sleeves to architect solutions, shape demand with business stakeholders, and drive adoption of enterprise data platforms. This role operates at the intersection of business strategy and technical execution, ensuring the Channel BU leverages data as a strategic asset for growth, efficiency, and innovation. Based in Bangalore, India, this role will partner closely with the NA based Data & Analytics product owner, Channel BU leadership, global DIA teams, and cross-functional stakeholders across AMER, EMEA, and APAC regions.

Tasks And Responsibilities Team Leadership & Delivery

• Lead and develop a team of 8–12 analytics engineers, data engineers, and data scientists.
• Own delivery of the Channel BU analytics portfolio, including capacity planning, backlog prioritization, sprint execution, and roadmap commitments.
• Establish Agile practices and drive predictable, high-quality delivery.
• Manage performance through goal setting, coaching, development planning, and succession planning.
• Support hiring, onboarding, retention, and growth of India-based analytics talent.
• Foster a culture of ownership, innovation, continuous learning, and operational excellence.
• Drive KPI, SLA, QBR, and continuous improvement initiatives, ensuring effective issue resolution and operational maturity.

Channel Data Management

• Define and execute the Channel BU data and analytics roadmap.
• Oversee development and maintenance of data pipelines, ETL/ELT processes, and data models supporting POS, inventory, backlog, pricing, and solution center analytics.
• Manage Databricks architecture, including dimensional modeling and scalable data-loading strategies.
• Ensure data quality, governance, security, lineage, and compliance in partnership with enterprise teams.
• Lead migration from legacy platforms to the OneData Platform (Databricks), eliminating duplication and ensuring business continuity.

Analytics & Self-Service BI

• Deliver dashboards, analytics solutions, and AI-powered tools for leadership, sales, customer care, pricing, and strategy teams.
• Build scalable semantic models and self-service analytics capabilities using Power BI and related technologies.
• Ensure governed analytics through security controls, metadata management, and version control.
• Translate data into actionable insights and continuously improve solution adoption, performance, and user experience.

AI & Data Science

• Lead development and deployment of AI/ML solutions, including forecasting, customer segmentation, pricing intelligence, data optimization, and automation use cases.
• Partner with business and AI leaders to identify opportunities, build business cases, and deliver measurable value.
• Oversee the full data science lifecycle from problem definition through deployment and monitoring.
• Ensure compliance with enterprise standards for AI governance, ethics, privacy, and regulatory requirements.

Stakeholder Management

• Act as the primary analytics partner for Channel BU, aligning priorities and communicating delivery progress.
• Translate business needs into scalable analytics and AI solutions in collaboration with stakeholders, process owners, and the broader DIA organization.
• Establish demand management processes and track business value delivered.
• Promote Data & AI literacy and self-service adoption across the organization.
• Collaborate effectively with global stakeholders across AMER, EMEA, and APAC.

What Your Background Should Look Like

• Bachelor's degree in Engineering (BE/BTech), Computer Science, Statistics, Mathematics, Economics, or related quantitative field. Master's degree preferred.
• 10+ years of progressive experience in data analytics, business intelligence, data engineering, or data science roles.
• 3+ years of direct people management experience leading teams of 5+ resources, with a proven track record of building and developing high-performing analytics teams.
• 5+ years of hands-on experience with BI tools (Power BI, Tableau) including dashboard design, semantic data modeling, and performance optimization.
• 3+ years of experience with cloud data platforms (AWS Redshift, S3, Databricks, Azure) and modern data warehouse architectures.
• 2+ years of experience with Python, R, or similar languages for data analysis, automation, and/or machine learning.
• Demonstrated experience delivering AI/ML or data science projects from ideation through production deployment.
• Strong SQL skills and deep understanding of data warehousing concepts (star/snowflake schemas, ETL/ELT, incremental loading). Ideal Soft Skills
• Business Acumen: Ability to translate business needs into data-driven strategies and deliver measurable impact. Experience in Channel/Distribution business models is a strong plus.
• Delivery Management: Proven ability to manage multiple concurrent workstreams, balance competing priorities, and deliver on committed timelines using Agile methodologies.
• Leadership & Influence: Strong ability to engage, communicate, and influence senior executives and cross-functional teams across geographies and time zones.
• Technical Depth: Hands-on fluency with modern data stack — data engineering, analytics, and data science — sufficient to guide architecture decisions, conduct code reviews, and unblock the team.
• Change Management: Experience driving organizational change, legacy system modernization, platform migration, and data literacy initiatives.
• Communication: Exceptional written and verbal communication skills; ability to present complex analytical findings to executive audiences through data storytelling. Technical background
• Data Platforms: Databricks, AWS S3, Azure, Snowflake with deep understanding of star/snowflake schemas, fact/dimension tables, and data warehousing concepts
• ETL/ELT & Orchestration: Azure Data Factory, AWS Glue, dbt, Apache Airflow, or similar pipeline orchestration tools
• Data Governance: Data lineage, cataloging, quality frameworks, and metadata management
• BI Tools: Power BI (DAX, Power Query, semantic models, row-level security) and Tableau (LOD expressions, Tableau Prep, Tableau Server/Cloud)
• Data Modeling: Semantic model design, star/snowflake schema optimization, incremental refresh strategies
• ML Platforms: Databricks MLflow, AWS SageMaker, Azure ML, or similar
• Generative AI: Familiarity with Microsoft Copilot, Databricks AI/Genie, Salesforce Einstein, LLM-based solutions, and prompt engineering

Competencies SET : Strategy, Execution, Talent (for managers)