Job Summary

Turns analytics into direction for International Business Unit (IBU) digital engagement and builds the Artificial Intelligence (AI) and automation that lets the function scale without adding headcount in step with volume. The primary focus is Enterprise Websites, the IBU affiliate portfolio delivered through the Unified Experience (UE) website programme, with other digital engagement channels also in scope. The role carries two connected mandates.

First, it owns the measurement layer for these properties: reporting, cross-affiliate performance, and the insight that shapes where the strategy invests next. Second, it designs and ships AI and agentic solutions across the Digital Engagement (DE3) operating model, targeting the repetitive, high-volume work that would otherwise force linear hiring as scope grows.

This is a hands-on role for someone equally comfortable in Google and Adobe analytics tooling and in low-code or agentic build environments. The right person moves from a data question to a clean, self-serve dashboard, and from a manual operational bottleneck to a working AI solution that removes it. They partner closely with affiliate leads, the wider Digital Engagement (DE3) team, and technology stakeholders to make sure both the intelligence and the automation are accurate, adopted, and tied to a real business outcome.

Key Responsibilities

IBU Analytics and Strategy Intelligence

- Own recurring performance reporting and insight packages for IBU Enterprise Websites and other priority digital engagement properties.

- Translate strategy questions from IBU and Digital Engagement (DE3) leadership into structured analysis, connecting behavioral, journey, and Voice of Customer (VoC) data to clear recommendations.

- Establish consistent measurement methodology across affiliates so performance can be compared fairly and trends read reliably.

- Surface where digital engagement is and is not working across markets, and frame the trade-offs for leadership decisions.

Dashboard and Visualization Build

- Build dashboards in Adobe Customer Journey Analytics (CJA), Google Analytics (GA4), Power BI, Looker Studio, or comparable tools, reflecting experience health, channel performance, and conversion across IBU Enterprise Websites and affiliate properties.

- Design dashboards around the decisions each audience needs to make, so stakeholders can answer their own questions without waiting on a manual pull.

- Maintain a cross-affiliate experience health dashboard, keeping metrics current and visualizations accurate as markets and properties are added.

- Design self-serve, user-centric dashboards,



iterating on them based on affiliate and leadership feedback, with a focus on clarity and usability for non-technical audiences.

- Document dashboard logic, data sources, and refresh cadence so reporting has operational continuity independent of any single person.

AI and Automation Solution Development

- Identify the manual, repeatable, or high-volume tasks across Digital Engagement (DE3) operations where AI or agentic solutions can remove effort and prioritize them by scale impact.

- Design, build, and ship AI-enabled and agentic solutions using low-code and no-code platforms, integrating with the existing Adobe Experience Cloud and Digital Engagement (DE3) stack rather than building from scratch.

- Prove each solution against a baseline, measuring hours returned, throughput gained, or headcount avoided, so scaling is evidenced rather than assumed.

- Document, hand over, and support adoption of shipped solutions so they run reliably without the builder in the loop.

Applied AI and Emerging Technology

- Apply Large Language Model (LLM) based assistants and other generative AI tools within day-to-day analytics, reporting, and operational work to raise output per person.

- Track emerging AI technologies, including current models, agentic frameworks, and vendor capabilities, assess their fit for Digital Engagement (DE3) operations, and pilot the ones that show clear leverage.

- Champion responsible and compliant AI use across the team, sharing reusable prompts, patterns, and workflows so gains spread beyond a single person and hold up against data and content review requirements.

Enablement and Operating Model

- Build the data foundations, definitions, and reusable assets that let the wider team self-serve rather than wait on manual pulls.

- Partner with affiliate and technology stakeholders to embed analytics and AI solutions into day-to-day operations.

- Collaborate closely with the Enterprise Website Initiative (EWI) and the Global Search Capability team, aligning measurement, insight, and AI solutions with how the Enterprise Websites are built, run, and optimized.

- Keep a live view of where AI can extend the operating model next, feeding the roadmap for scaling capability ahead of demand.





Success Looks Like

- IBU digital engagement decisions are informed by reliable, comparable data rather than anecdote or single-market views.

- Repetitive operational work is progressively absorbed by AI and automation, so scope can grow without a matching rise in headcount.

- Each shipped AI solution has a measured before-and-after, with time or capacity returned that can be pointed to.

- Analytics and solutions are trusted and used across affiliates, not one-off builds that decay after handover.

- Stakeholders answer routine questions through self-serve dashboards rather than one-off analyst requests.

- Leadership has a clear, current picture of where automation can scale the function next.

Core Skills

- Digital analytics execution across Adobe Customer Journey Analytics (CJA), Adobe Analytics, and Google Analytics (GA4), or comparable

- Designing self-serve, user-centric dashboards for non-technical audiences

- Building AI-enabled and agentic solutions using low-code and no-code platforms

- Fluency applying generative AI assistants such as Claude and Microsoft Copilot as day-to-day force multipliers across analysis, drafting, and build work

- Structured analysis, pattern recognition, and clear framing of findings for decision-makers

- Translating operational bottlenecks into scoped, buildable automation

- Measurement discipline: baselining, quantifying impact, and documenting for handover

Basic Requirements

- Bachelors degree in Analytics, Data Science, Computer Science, Digital Marketing, or a related field.

- Two or more years of experience spanning digital analytics and hands-on solution-building, ideally in a digital engagement, marketing operations, or web experience context.

- Proficiency in Adobe Customer Journey Analytics (CJA) and Adobe Analytics, Google Analytics (GA4), including custom explorations, segments, and event-level reporting, or demonstrable equivalent.

- Demonstrated experience building and shipping AI-enabled or automation solutions using low-code, no-code, or agentic platforms, with a working example that reached production.

- Demonstrated fluency using generative AI assistants, for example Claude and Microsoft Copilot, to accelerate analysis, prototyping, and documentation, with a practical sense of where they add leverage and where human judgment is still needed.

- Ability to define impact metrics and prove that a solution returned measurable time, throughput, or capacity.

- Strong attention to data accuracy and a track record of catching quality issues before they surface downstream.

📌 Digital Engagement Analytics Consultant (Bengaluru)
🏢 Eli Lilly
📍 Bengaluru