Teams at Morningstar

Build scalable data pipelines and investment data platforms supporting quantitative research, backtesting, and deployment of multi-asset investment models. Responsibilities include processing market and fundamental data, integrating third-party providers, maintaining databases and research datasets, automating workflows with CI/CD and infrastructure-as-code, and supporting cloud-based and event-driven architectures. The role collaborates closely with quantitative researchers and portfolio managers and explores AI/ML and generative AI applications.

Own the roadmap and backlog for managed investment calculation capabilities. Translate financial methodologies and business needs into detailed specifications, user stories, and acceptance criteria. Analyze investment datasets using SQL, prototype and validate calculations, investigate discrepancies, and coordinate with research, engineering, QA, and stakeholders. Ensure calculation accuracy, data quality, traceability, release readiness, and effective communication across global teams.

Manage investment fund data quality, regulatory portfolio reporting, and fund categorization initiatives across global markets. Process and validate managed investment data, resolve complex stakeholder queries, identify automation and process improvement opportunities, and create operational requirements for scalable tools. Serve as a subject-matter expert on investment data, coach junior analysts, coordinate training, and ensure accurate, timely data delivery while supporting continuous improvement through Lean Six Sigma and Agile methods.