Associate Director - CAS AI Analytics Platform Engineering & AI Solutions

Corporate Audit Services Organization Overview

Corporate Audit Services (CAS) is an independent, objective audit and consulting function driven by a commitment to add value and enhance the operations of Eli Lilly and Company. CAS's mission is to support the company in achieving its objectives by employing a systematic, disciplined approach to evaluate and improve the effectiveness of risk management, control, and governance processes.

Position Description

This position builds and delivers best-in-class, end-to-end analytics solutions on Microsoft Fabric, the foundation of the CAS data platform. Working across the full lifecycle, from data engineering, warehousing, and ELT through semantic models, Power BI, and Fabric apps, the individual creates and evolves a portfolio of Fabric solutions that turn CAS data into trusted, self-service intelligence.

A core focus is building AI Ready Semantic Models, the governed, contextual data layer that grounds Claude and AI agents in trusted CAS data. Partnering directly with CAS audit teams and stakeholders, the individual translates business needs into working solutions, drives efforts to completion, and grows adoption across the function, delivering high-quality, well-governed solutions within the CAS data architecture and data engine standards.

The individual also helps innovate how CAS builds and automates, leveraging Claude Code and beginning to apply agentic frameworks to accelerate development and automate CAS audit and Data Analytics operations. Above all, this is a hands-on builder who thrives on a team of doers, collaborates openly, sets and evolves standards alongside peers, and partners across Finance and the broader Lilly organization to deliver where it creates the most value.

Success in this role is as much about how the work gets done as what gets built. This is a highly collaborative, hands-on team of builders who share openly, support one another, and put the team's success first. The individual brings an ownership mindset and a high personal bar, communicates with clarity and empathy, stays humble and curious, and builds trust across CAS and its partners, contributing to a positive culture where people do their best work.

Primary Position Responsibilities

Fabric Data Engineering & ELT

• Design, build, and maintain scalable data solutions on Microsoft Fabric, spanning lakehouses, warehouses, and a medallion architecture (Bronze, Silver, and Gold layers).

• Engineer the full ELT lifecycle, building ingestion, transformation, and refresh pipelines with Fabric notebooks and configuration-driven frameworks that are scalable, reusable, and maintainable.

• Build and maintain data orchestration across solutions, coordinating pipelines, dependencies, scheduling, and refresh.

• Refactor and migrate existing solutions onto the Fabric platform, following established governance and deployment standards.

• Apply CI/CD, Git version control, and automated testing that bring engineering rigor and repeatability to solution development.

• Uphold and extend the CAS data architecture and governance frameworks, keeping solutions secure, well-structured, and maintainable at enterprise scale.

Semantic Models, Power BI & Fabric Apps

• Build data engines and semantic models on Fabric to the CAS data engine standards, primarily using Direct Lake, with strong attention to DAX and model performance for governed, high-performance consumption by Power BI, Fabric apps, and Claude.

• Develop AI Ready Semantic Models, establishing the holistic contextual layer within the semantic model (definitions, relationships, and business meaning) that makes it consumable by large language models and grounds Claude in trusted CAS data.

• Leverage Claude, MCP, and Claude Code to build and enrich AI Ready Semantic Models and to innovate how CAS delivers AI-grounded analytics.

• Own Power BI solution delivery, building dashboards, executive visualizations, and reporting that make data accessible and actionable for stakeholders.

• Innovate new Fabric app solutions, designing and building Fabric-native applications that extend how CAS delivers and consumes data.

• Architect self-service analytics that enable stakeholders to explore data without ongoing developer support.

• Establish enterprise deployment patterns, including shared datasets, deployment pipelines, and version control that bring engineering rigor to analytics delivery.

Solution Delivery & Stakeholder Partnership

• Partner with CAS audit leadership to understand their priorities, workflows, and process pain points, translating them into analytics and automation solutions that measurably improve how audits are executed.

• Act as a trusted advisor, proactively identifying opportunities to streamline audit processes and bringing forward solutions rather than waiting for requirements.

• Maintain and evolve a portfolio of Fabric solutions, continuously improving performance, usability, and reliability.

• Deliver organizational reporting and analytics dashboards for business partners, leaders, and stakeholders.

• Orchestrate work delivery through Smartsheet, managing intake, prioritization, tracking, and delivery metrics.

• Operate in an Agile delivery model, driving continuous improvement, adoption, and business value.

Automation & Agentic Innovation

• Automate CAS audit processes, building automation solutions for auditors that reduce manual effort and improve consistency across audit execution.

• Automate Data Analytics operations, streamlining intake, delivery, and platform tasks to increase team efficiency and quality.

• Leverage Claude Code and AI-assisted development to accelerate the build and maintenance of Fabric and automation solutions.

• Pilot autonomous solutioning, applying agentic frameworks to automate build, testing, and operational tasks as this emerging capability matures.

• Contribute to the CAS Claude Skill strategy, helping create and maintain reusable skills that encode Fabric, solution, and automation capabilities.

• Pioneer and help define how agentic approaches evolve into AI-native CAS solutions over time, establishing early patterns the team will build on.

Technical Leadership & Innovation

• Set, follow, and evolve technical standards alongside the team, contributing best practices, design patterns, and reusable templates to the shared Confluence repository referenced across Data Analytics and CAS.

• Lead solution design for complex analytics and data challenges, shaping the approach and bringing peers along collaboratively.

• Own delivery end to end, driving efforts to completion and taking accountability for quality, performance, and outcomes.

• Contribute to solution and code reviews, exchanging feedback with peers to keep quality, consistency, and governance high across the team.

• Advance how CAS builds, evaluating and piloting emerging Fabric, analytics, and agentic capabilities and sharing what works so the whole team benefits.

• Share knowledge and enablement, helping build collective capability on Fabric, semantic modeling, Power BI, and AI tools.

Basic Qualifications / Requirements

• Bachelor's Degree in Business Analytics, Data Science, Computer Science, Information Systems, Data Engineering, or related field, or equivalent experience.

• 5+ years of relevant professional experience in data engineering, analytics, or data solution development within a global, matrixed organization.

• Qualified applicants must be authorized to work in the United States on a full-time basis. Lilly will not provide support for or sponsor work authorization or visas for this role, including but not limited to F-1 CPT, F-1 OPT, F-1 STEM OPT, J-1, H-1B, TN, O-1, E-3, H-1B1, or L-1.

Additional Skills / Preferences

• Demonstrated experience leading end-to-end data solution delivery and setting technical standards that others follow, including through solution and design reviews.

• Hands-on Microsoft Fabric experience (preferred) or a similar cloud data platform, including Lakehouse and warehouse design, medallion architecture, notebooks, and the full ELT lifecycle.

• Strong semantic modeling proficiency, including advanced DAX, model design, and performance optimization.

• Power BI and Fabric app delivery as a presentation layer, including dashboards, executive visualizations, and Fabric-native applications.

• Data engineering languages and tools (Python, PySpark, SQL) and configuration-driven, automated data pipelines across diverse source systems.

• Power BI and Fabric app delivery as a presentation layer, including dashboards, executive visualizations, and Fabric-native applications.

• End-to-end solution delivery from requirements through deployment, adoption, and iteration.

• Stakeholder partnership, translating business or audit needs into working solutions and driving adoption.

• Process automation experience, building automations that reduce manual effort for business or operations teams.

• CI/CD, Git, version control, testing, and DataOps for analytics and data engineering.

• Pipeline monitoring and operational support patterns, including alerting and reliability practices.

• Exposure to Claude Code, or strong interest in adopting AI-assisted development to accelerate solution building.

• Interest in agentic AI frameworks and autonomous solutioning, with a desire to help build this emerging capability for CAS.

• Structured data formats (JSON, YAML) and data-grounding patterns for AI.

• Data access and security controls to govern data and AI access.

• Data privacy and AI governance awareness, including responsible AI practices.

• Regulated enterprise experience with attention to data governance and auditability.

• Agile delivery methodologies and work-management tooling such as Smartsheet.