Build a multi-year data roadmap with clear priorities, owners, funding needs and measurable outcomes.
Set up data governance: ownership, definitions, quality rules, access controls and compliance with LGPD and Lilly policies.
Standardize KPIs and metric definitions so every report tells the same story.
Manage internal and external data sources, including contracts, costs and refresh rules.
Data architecture and platforms
Own the Brazil data architecture, from ingestion and storage to modeling and serving layers.
Work with Tech@Lilly to choose platforms and tools that meet enterprise standards and can scale.
Lead adoption of the Enterprise Data Backbone, and retire local pipelines and duplicate data stores when a standard option exists.
Keep pipelines reliable, documented, monitored and cost aware.
Prepare data foundations for AI: clean, well described, secure and easy to find.
Decide what to build locally and what to reuse from global teams.
Reporting and insight delivery
Lead the redesign and consolidation of dashboards into a small set of enterprise-standard reporting products.
Retire legacy reports and set clear rules for when a new dashboard is justified.
Define service levels for reporting, including refresh times, data quality, support and release cycles.
Translate complex data into clear insights for Commercial, Medical, Finance, Corporate Affairs and Operations.
Enable self-service analytics with certified datasets, shared semantic models and simple guidance.
Represent data and reporting topics in Brazil leadership forums and planning cycles.
AI and advanced analytics
Define the AI and advanced analytics agenda for Brazil, tied to real business use cases and value targets.
Rank use cases by value, feasibility and data readiness, and stop those that do not deliver.
Partner with global teams and Tech@Lilly to bring approved AI tools and models into daily work.
Set guardrails for responsible AI, including data privacy, model validation, human review and audit trails.
Track adoption and business impact of each AI solution, not only delivery.
Test new methods in small pilots and scale only what works.
Change management and capability building
Lead a change plan for each major data initiative, with stakeholder mapping, communication, training and adoption tracking.
Guide teams and business partners through the move from legacy tools to new platforms and ways of working.
Build data literacy programs for commercial, medical and corporate teams.
Name data champions in each area and run regular feedback loops.
Measure adoption with clear indicators, such as active users, retired reports and use of certified data.
Team, vendors and partners
Lead, coach and develop a team across data architecture, reporting and advanced analytics.
Manage vendor and offshore teams for quality, timing and cost.
Manage budget, capacity and priorities across the data portfolio.
Align roadmaps with global BI&A, GCDP, Tech@Lilly, OCE, CRM and Digital Business Hub teams.
MINIMUM REQUIREMENTS
Minimum 8 years of experience in data, analytics, BI or commercial operations.
Minimum 3 years leading data strategy, architecture or platform work.
Minimum 3 years of people leadership experience (direct reports and/or matrix leadership).
Proven delivery of data and IT projects on modern cloud and BI platforms.
Solid knowledge of data modeling, governance, data quality and security.
Working knowledge of AI and machine learning, and how to bring them to production responsibly.
Strong vendor, budget and portfolio management skills.
Demonstrated ability to influence senior stakeholders across commercial and medical functions.
Fluent in English and Portuguese (written and spoken).
ADDITIONAL PREFERENCES
Change-management experience, with a track record of guiding teams through platform and process transitions.
Experience in pharma or another regulated industry.
Global or multi-market data program experience.
Understanding of pharma commercial, medical and omnichannel data, such as CRM, sales and market data.
Hands-on knowledge of BI tools, SQL and cloud data platforms.
Curiosity about AI and data trends, with the discipline to turn them into practical solutions.
Ability to explain technical topics to non-technical leaders.
Bias toward measurable business outcomes.
Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.
Lilly does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status.
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