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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Head of Data Operations, Direct Platform - **Company:** Morningstar, Inc. - **Location:** Chicago, IL, United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Big Data, Cloud Computing, Data Infrastructure, Reference Data, DataOps, Workflow Management Systems, Data Strategy, Information Technology, Data Analytics, Data Management, Legacy Systems - **Published:** September 19, 2026 - **Apply:** https://jobs.localjobnetwork.com/apply/add/88387826/1 ## About the Role * 10+ years of executive leadership experience leading large-scale data acquisition, operations, technology, or transformation organizations, with accountability for both operational performance and modernization initiatives. * Strong understanding of financial, investment, reference, and/or market data ecosystems, including the operational processes required to acquire, manage, enrich, and deliver high-quality datasets at scale. * Proven track record leading large-scale transformation efforts leveraging automation, AI-enabled capabilities, workflow modernization, and technology-driven process redesign to improve scalability, efficiency, quality, and productivity. * Experience leading large, globally distributed organizations through significant organizational change, operating model evolution, and continuous improvement initiatives. * Demonstrated ability to partner effectively across Product, Technology, Data Strategy, Research, and Commercial organizations to translate strategic priorities into operational and technology outcomes. * Exceptional leadership, communication, stakeholder management, and change leadership skills, with the ability to influence senior executives and drive enterprise-wide impact. * Experience implementing or sponsoring investments in AI, automation, workflow tooling, advanced analytics, and operational technologies within complex enterprise environments. * Willingness to travel as needed to engage with global teams and stakeholders, including operations centers in Madrid and Mumbai. * Bachelor's degree in Finance, Business, Computer Science, Engineering, or a related field; advanced degree preferred. Preferred Experience * Experience leading technology-enabled transformation within financial services, market data, investment data, reference data, or adjacent information services organizations. * Experience managing or sponsoring large-scale investments in data acquisition technology, workflow platforms, automation capabilities, and AI-powered operational solutions. * Familiarity with modern data platforms, cloud-based technologies, and enterprise-scale data operations environments. ## Description For the Head of Data Operations, we are seeking a transformational leader to oversee Morningstar's global data acquisition, operations, and collection technology ecosystem. This executive will lead a large-scale global organization (~700 people) while driving modernization of the platforms, workflows, and operating models that support data collection, enrichment, quality management, and delivery. Reporting to the Chief Technology Officer of the Direct Platform, the Head of Data Operations will partner closely with Data Strategy, Product, Research, Engineering, and Architecture leaders to execute Morningstar's data acquisition roadmap, accelerate automation and AI-enabled capabilities, and establish a scalable operating model capable of supporting the next generation of investment data products. The role requires a unique blend of operational leadership, technology transformation expertise, and strategic vision to drive innovation while ensuring operational excellence across the global data ecosystem. Responsibilities Data Operations Leadership * Lead a global organization responsible for acquiring, managing, enriching, and delivering investment, reference, and market data at scale. * Partner with Data Strategy, Product, and Research leaders to execute the enterprise data acquisition strategy and roadmap. * Translate strategic data priorities into scalable operational capabilities, processes, and technology solutions. * Drive organizational agility by rapidly adapting data acquisition approaches to evolving market opportunities, regulatory requirements, and client needs. * Lead initiatives that improve accuracy, productivity, efficiency, and scalability while maintaining appropriate quality standards for each data product. * Foster a high-performance culture focused on accountability, innovation, continuous improvement, and client impact. Data Platforms & Technology Transformation * Lead the evolution of Morningstar's data collection, acquisition, and production ecosystem, establishing a vision for modern, scalable, and highly automated operations. * Drive investment decisions and prioritization for collection platforms, workflow tools, AI-enabled solutions, and operational technologies. * Partner with Engineering and Architecture leaders to modernize legacy systems and accelerate automation across the data lifecycle. * Champion the adoption of AI, advanced analytics, and emerging technologies to improve operational effectiveness and scalability. * Establish operating metrics, performance frameworks, and management disciplines to continuously improve efficiency, quality, and throughput. * Monitor emerging technologies and industry best practices to ensure Morningstar remains at the forefront of data acquisition and operational innovation. Governance, Risk & Cross-Functional Leadership * Execute data governance policies and operational frameworks established in partnership with Data Strategy, Product, Risk, Compliance, and other key stakeholders. * Ensure data collection, management, and operational processes comply with applicable regulatory, privacy, and risk requirements. * Build strong partnerships across Product, Research, Data Strategy, Technology, Commercial, and Client-facing organizations. * Serve as a trusted advisor to senior leadership on operational strategy, transformation priorities, investment decisions, and organizational effectiveness. * Champion a data-driven, customer-centric culture across the enterprise while promoting collaboration and accountability., Morningstar's hybrid work environment gives you the opportunity to collaborate in-person each week as we've found that we're at our best when we're purposely together on a regular basis. In most of our locations, our hybrid work model is four days in-office each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you'll have tools and resources to engage meaningfully with your global colleagues. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Hacking Your Vacation: Using Data for Fun](https://www.wearedevelopers.com/videos/585-hacking-your-vacation-using-data-for-fun) - [Big Business, Big Barriers? 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