Job Link: https://ziphire.hr/job/85bdf7ba-cbba-492a-a140-966ec78fe694 TE Connectivity Ltd., is a $16 billion global technology and manufacturing leader creating a safer, sustainable, productive, and connected future. For more than 75 years, our connectivity and sensor solutions, proven in the harshest environments, have enabled advancements in transportation, industrial applications, medical technology, energy, data communications, and the home. With 80,000 employees, including more than 8,000 engineers, working alongside customers in approximately 140 countries, TE ensures that EVERY CONNECTION COUNTS. Learn more at www.te.com and on LinkedIn, Facebook, WeChat and Twitter. Job Overview At TE we strongly believe that data and analytics are strategic drivers for future success. We are investing significantly in building our advanced analytics team. The Analytics team at TE is responsible for driving organic growth by leveraging big data and advanced analytics. The team reports to the VP and Chief Data Officer at TEIS, works closely with the SVP of Corporate Strategy, and has regular interactions with the company’s C-Suite. This Senior Data Engineer position will directly report to the Director of Analytics Insights. We are on an exciting journey to build and scale our advanced analytics practice; in this position you will apply your skills to unlock opportunities and enable top strategic priorities for TE. You will be working on problems that require advanced analytics applications to create value for engineering function and will impact business units that span through multiple geographic areas. Responsibilities Design and build robust data pipelines and feature stores that powers our AI products. Analyse data requirements, understand complex data sources, and partner with architects to determine the best methods to extract, transform, and load data into data platform. Lead conversations with business or functional teams to translate user requirements into reusable and cost-efficient data acquisition methodologies for AI products. Be the key anchor for data extraction, preparation and hosting processes representing the AI team. Data expert for engineering datasets used by data scientists working on various use cases. Perform functional and stress testing on data models and extraction jobs to ensure that design is optimized for performance, scale, and reusability. Manage foundational data administration tasks such as scheduling jobs, troubleshooting job errors, identifying issues with job windows, assisting with database backups and performance tuning. Ensure data quality throughout entire development process, including audits and feedback loops to sources of truth. Create or update technical documentation for transition to support teams. Mentor junior data engineers

• Architect, build, and own scalable ELT pipelines, data orchestration, and the enterprise data warehouse. • Lead requirements analysis and solution design, ensuring an end-to-end view of the data ecosystem. • Own the operation, reliability, and monitoring of production data pipelines. • Drive data projects from ideation through execution, acting as the primary owner and decision-maker. • Design and implement standardized, analytics-ready data models that support reporting, experimentation, and advanced analytics. • Build reusable ingestion and integration frameworks for internal systems and external partners. • Establish and continuously improve automation, orchestration, and observability across data workflows. • Define and enforce data engineering standards, including modeling, testing, documentation, and deployment. • Integrate AI-enabled tooling and agents where appropriate to improve productivity and data operations. • Maintain high-quality technical documentation for architecture, pipelines, and processes. • Act as a technical mentor for Data Engineers and Analytics Engineers. • Provide guidance on design decisions, code quality, and architectural trade-offs. • Lead by influence—reviewing designs, unblocking teams, and driving alignment. • Support the maturation of the data team by modeling best practices and ownership mindset.

• Develops and maintains software solutions for business operations • Performs analysis, design, coding, debugging, testing, and support of software applications • Works with Agile Program Manager and Digital Product Manager to capture stakeholder requests • Completes software development work including design, coding, and testing • Manages engineering risks and communicates issues • Supports business units resolving user questions after production support

• Work as part of a GCP implementation team from concept to operations • Provide deep technical subject matter expertise for successful deployment of Data Platform automation • Provide technical guidance, mentorship, and code-level support to the development team • Drive effective and efficient delivery, focusing on speed, identifying risks, implementing mitigation/contingency plans and test/compare competing solutions • Design and build production data engineering solutions to deliver our pipeline patterns using GCP Services • Ensure data quality, maintain profiles of data products, monitor system performance