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At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve. This is hard, urgent, selfless work—but it’s work worth doing. If you’re driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us. Integrated Risk Management Program Overview 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. IRM enables faster, better informed decision-making that protects what matters most: our operations, reputation, and ability to deliver life-saving medicines to patients. This integrated approach creates a coordinated and proactive system that helps Lilly stay resilient and agile as we continue reaching more patients than ever before. Position Description The Integrated Risk Data Engineer serves as the technical expert who owns the data foundation powering risk intelligence across the enterprise. This role independently leads data architecture and engineering initiatives from conception through delivery, integrating fragmented systems, designing unified data pipelines, and ensuring risk leaders have access to complete, accurate, and timely risk data. Working within the centralized IRM Analytics team, you will define and implement the Microsoft Fabric architecture and data governance framework that connects disparate risk platforms, including ServiceNow GRC, assurance systems, enterprise applications, and business-specific tools, into cohesive data ecosystems that enable comprehensive risk visibility. This role requires depth and breadth of expertise in data engineering, with recognized proficiency that positions you as a key technical resource within the IRM function. You will own the design and maintenance of robust data infrastructure using Microsoft Fabric's medallion architecture, lead data pipeline and transformation initiatives, and establish data governance standards that ensure data quality, security, and accessibility across all IRM functions. Balancing hands-on delivery with standards definition and technical leadership, you will transform how risk data flows through the organization—breaking down historical silos and creating analytics and AI-ready datasets that enable advanced analytics, real-time monitoring, and predictive risk intelligence. Primary Position Responsibilities Data Architecture & Infrastructure Leadership 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 Solution Delivery & Technical Excellence 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 Operational Excellence & Standards Definition 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 Build strategic relationships with Tech@Lilly (IT), risk platform administrators, and business data owners to identify and resolve data integration challenges that impact the broader IRM function Strategic Partnership & Influence Build and maintain strategic relationships with risk data owners, assurance function partners, and enterprise data teams to identify internal customer requirements and opportunities to improve data availability, quality, and integration Lead standardization of data definitions, taxonomies, and integration patterns across risk functions, influencing technical decisions that enable more effective cross-functional analytics Lead the upskilling of IRM team members and business partners in data engineering concepts, serving as a subject matter expert and contributing to data literacy across the organization Stay current on emerging data engineering technologies, practices, and tools, evaluating and applying relevant innovations to enhance Lilly's risk data capabilities Basic Qualifications/Requirements 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. Additional Skills/Preferences Expert proficiency with Microsoft Fabric (preferred) or similar cloud data platforms (Azure Data Factory, Synapse Analytics, Databricks), with ability to define architecture standards and best practices Advanced SQL and Python/PySpark skills, with hands-on experience building data pipelines in Spark notebook environments (Fabric, Databricks, or similar), using Git-based version control Experience integrating LLM/API-based workflows (RAG, embeddings, enterprise LLM gateways), with interest or exposure to agentic tool-calling protocols such as MCP Demonstrated experience independently leading data engineering projects from planning through delivery, including architecture design and standards definition Demonstrated ability to translate complex business requirements into scalable technical data solutions with sound decision-making within functional guidelines
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.