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 OverviewResponsible for designing and establishing the solution architecture for analytical platforms and/or data-enabled solutions.Has broad understanding of the entire data and analytics eco-system of tools and technologies, with hands-on experience across all three core data domains of data science, data engineering, and data visualization. Responsible for fleshing out the details of the end-to-end component architecture being implemented by the team. Contributes to the team\'s development velocity, if necessary. Understands how an organization\'s data platform integrates within the overall technical architecture. Understands the business purpose the role fulfills, and the roadmap for the lifecycle of an organization\'s systems. Sets the direction and establishes the approach for integrating information applications and programs.Roles & ResponsibilitiesThe Sr. Marketing Data & Analytics Analyst will be responsible for TE Connectivity\'s strategic marketing analytic solutions. This position will conduct analysis and generating business insights of global demand waterfall performance, campaign performance, website activity, product analysis, and customer analysis revenue for the business unit. This position will also be responsible for conducting regularly scheduled and ad hoc analyses that dive deep into the data to uncover the hidden insights and recommendations that will help TE go beyond explaining what happened, but rather inform us what we should do next. Working cross-functionally with internal marketing teams and external creative and digital media agencies to translate marketing business questions into insights that will improve marketing performance.The ideal candidate will have extensive experience generating data insights and analyzing B2B marketing automation platforms to enable TE Connectivity to grow our marketing effectiveness and ROI. This includes the full data analysis lifecycle from collection, analysis, sourcing, integration, storage and automated reporting. Candidates will have demonstrated the ability to understand specific data needs for analytic and reporting solutions, and then have aptitude in the development of associated data models to support data visualization, reporting and analytics.
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