• Actionable Insight: Generate compelling and actionable insights from complex, multi-source marketing data sets that directly inform channel investment, campaign design, and pipeline strategy. • Stakeholder engagement: Establish strong collaborative relationships with marketing leaders and operators across demand gen, partner, field, product marketing, and brand, delivering high-impact analytics initiatives that translate loose, evolving requirements into clear deliverables. • Attribution & Measurement: Design, build, and maintain the attribution framework for UpGuard – spanning first and multi-touch attribution and incrementality testing – and clearly communicate the trade-offs and assumptions behind each lens. • Channel & Program Analytics: Develop a deep, first-principles understanding of channel logic across paid media, organic, content, lifecycle, partner, and field, and build the metrics, models, and dashboards that let each program owner self-serve their performance. • Data Products: Partner with the data engineering team to design, construct, and maintain foundational marketing data assets – translating loose marketing requirements into well-specified dbt models that the whole organisation can rely on. • Business Intelligence: Partner strategically with marketing stakeholders to provide robust self-service and conversational analytics capabilities, using design thinking principles to build user-friendly dashboards for funnel performance, channel ROI, partner sourced pipeline, and field event attribution. • Deep Dive analysis: Personally conduct thorough, hands-on, technical analysis to diagnose and solve the most significant marketing challenges – from channel saturation and diminishing returns to lead quality decay and campaign cannibalisation. • Commercial Analysis: Provide ongoing operational support to the commercial growth of the organisation, connecting marketing investment to pipeline, ARR, and payback in ways that finance and the executive team trust.

• Act as a bridge between Product, Customer Success (CS), Support, Pre-sales, Sales, and Technology • Perform initial assessment of requests, issues, and opportunities • Organize and structure information to support the Product Manager's decision-making • Triage items (enhancements, bugs, questions, customer requests, etc.) • Prepare clear, concise summaries of requests • Support organizing and running meetings (agenda, minutes, follow-up) • Log and track requests in tools such as Azure DevOps • Manage pending items, deadlines, and request statuses • Consolidate information from different teams • Assist the Product Manager with operational routines and backlog organization • Participate in client meetings to gather context • Ensure decisions and information are properly documented

• Overseeing and managing Jabil's critical data assets, ensuring data quality, integrity, and accessibility across various systems and platforms. • Developing and implementing data governance strategies. • Managing data lifecycles and leading initiatives to optimize data utilization for business insights and operational efficiency. • Design, implement, and maintain robust data management policies, procedures, and standards in alignment with Jabil's overall data strategy. • Lead efforts in data quality assurance, including defining data quality metrics, developing cleansing processes, and monitoring data accuracy. • Oversee the entire data lifecycle, from data acquisition and storage to archiving and disposal, ensuring compliance with relevant regulations and internal policies. • Collaborate with various business units to understand data requirements and translate them into effective data solutions and models. • Manage and optimize data repositories, databases, and data warehouses, ensuring high performance, scalability, and security. • Develop and implement data governance frameworks, including data ownership, stewardship, and access controls. • Provide technical leadership and mentorship to junior data professionals. • Evaluate and recommend new data management technologies and tools to improve efficiency and effectiveness. • Participate in cross-functional projects, providing data expertise and ensuring data integration across systems. • Document data processes, data flows, and system architectures comprehensively.

• Designs, develops, programs methods, processes, and systems to consolidate and analyze unstructured, diverse big data sources using machine learning and predictive modeling tools • Builds analytic models to identify and quantify solutions to business problems • Interprets and communicates insights and findings from analysis and experiments to client, service, and business managers • Determines probable future outcomes and recommends and delivers new business process improvements • Provides leadership and work guidance to less experienced personnel towards build of software programs, algorithms and automated processes to cleanse, integrate and evaluate large datasets