Associate Director - Integrated Risk Data Engineer

About the role

Lilly's Integrated Risk Management (IRM) program is a strategic enterprise initiative that transforms traditional risk management into a competitive advantage by uniting cross-functional expertise with cutting-edge analytics and technology. The Integrated Risk Data Engineer role is responsible for owning the data foundation powering risk intelligence across the enterprise.

Responsibilities

• Own the Microsoft Fabric architecture for IRM, defining standards, design patterns, and best practices that ensure scalable, maintainable, and high-performing data infrastructure across the risk ecosystem.
• Design, build, and maintain enterprise risk data pipelines using Microsoft Fabric with medallion architecture (bronze, silver, gold layers) that integrate data from multiple risk domains and enterprise systems.
• Architect and implement data engineering workflows using Fabric Data Factory, Synapse Data Engineering (Spark notebooks), and Dataflows Gen2 to consolidate fragmented risk data from ServiceNow GRC, SAP, Workday, SuccessFactors, assurance platforms, and other enterprise and function-specific systems.
• Design unified data models and Power BI semantic models that enable cross-functional risk analytics, ensuring data consistency, accuracy, and accessibility across all risk functions.
• Establish and own the data governance framework for IRM, including data quality standards, validation rules, monitoring processes, security protocols, and access controls that protect sensitive risk information while enabling appropriate data sharing.
• Serve as a key technical resource partnering with Analytics Developers, Architects, and Data Scientists to understand data requirements and deliver datasets that power dashboards, reports, predictive models, and risk assessments.
• Optimize data pipeline performance using Fabric's compute resources and data storage options (Lakehouse, Data Warehouse) to ensure stakeholders receive timely, accurate risk intelligence when decisions need to be made.
• Design and implement data observability and monitoring solutions that proactively identify and resolve data quality issues before they impact business decisions.
• Lead migration and integration initiatives as new risk technologies and platforms are adopted across the enterprise, independently owning project planning, solution architecture, and delivery.

Qualifications

• Bachelor's Degree in Computer Science, Information Systems, Data Engineering, or related field.
• 5+ years of relevant professional experience in data engineering, ETL development, or data integration, with demonstrated progression in responsibility and complexity.

Skills

• Expert proficiency with Microsoft Fabric (preferred) or similar cloud data platforms (Azure Data Factory, Synapse Analytics, Databricks).
• Advanced SQL and Python/PySpark skills, with hands-on experience building data pipelines in Spark notebook environments (Fabric, Databricks, or similar).
• Experience integrating LLM/API-based workflows (RAG, embeddings, enterprise LLM gateways).
• Experience designing and implementing medallion architecture or similar layered data lake design patterns at enterprise scale.
• Experience with ServiceNow platform, ServiceNow GRC, or other governance, risk, and compliance systems.
• Proficiency in dimensional modeling, star schema design, and data warehouse concepts.
• Experience in pharmaceutical, healthcare, or highly regulated industries with complex data governance requirements.
• Familiarity with Power Platform integration (Power Automate, Power Apps) with Fabric.
• Strong problem-solving skills with ability to anticipate, diagnose, and resolve complex data integration challenges.
• Proven ability to collaborate effectively with both technical teams and non-technical business stakeholders, translating technical concepts into business language.
• Detail-oriented with commitment to data quality and comprehensive documentation.
• Self-directed professional who works independently, takes initiative on complex problems, and proactively identifies opportunities for improvement.

Pay

$124,500 - $182,600

Schedule

Full-time