Associate Director - Integrated Risk Data Engineer - Eli Lilly
Data Engineer
We're looking for a Data Engineer focused on designing and building scalable technical solutions. This mid level role requires 5+ years of relevant experience.
About the role
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
Architect and build scalable, automated data solutions using Fabric pipelines and dataflows that reduce manual data preparation efforts and enable real-time or near-real-time risk monitoring capabilities
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
Independently respond to complex data requests from risk functions, producing clean, well-documented datasets in Fabric Lakehouses and Data Warehouses that support risk assessments, audits, investigations, and strategic initiatives
Anticipate and resolve complex data quality issues, working with source system owners and business partners to implement sustainable fixes that prevent recurrence
Define and maintain comprehensive documentation standards for data lineage, transformation logic, data dictionaries, and technical architecture that enable knowledge sharing and maintain institutional knowledge
Skills
llmragpythonsqlazureapache sparkdatabrickspower bi