Engineering and Quality

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Engineering and Quality - Lead Data Engineer

Requisition ID: 49580

Business Unit: Fitch Group

Category: Information Technology

Location: Monterrey, MX

Date Posted: Jul 25, 2026

Fitch Group is currently seeking a Lead Data Engineer based out of our Monterey, Mexico office.

As a leading, global financial information services provider, Fitch Group delivers vital credit and risk insights, robust data, and dynamic tools to champion more efficient, transparent financial markets. With over 100 years of experience and colleagues in over 30 countries, Fitch Group’s culture of credibility, independence, and transparency is embedded throughout its structure, which includes Fitch Ratings, one of the world’s top three credit ratings agencies, and Fitch Solutions, a leading provider of insights, data and analytics. With dual headquarters in London and New York, Fitch Group is owned by Hearst.

Fitch's Technology & Data Team is a dynamic department where innovation meets impact. Our team includes the Chief Data Office, Chief Software Office, Chief Technology Office, Emerging Technology, Shared Technology Services, Technology, Risk and the Executive Program Management Office (EPMO).Driven by our investment in cutting-edge technologies like AI and cloud solutions, we’re home to a diverse range of roles and backgrounds united by a shared passion for leveraging modern technology to drive projects that matter to our organization and clients. We are also proud to be recognized by Built In as a "Best Place to Work in Technology" 3 years in a row. Whether you're an experienced professional or just starting your career, we offer an exciting and supportive environment where you can grow, innovate, and make a difference.

Want to learn more about a career in technology and data at Fitch?

Join the Data Marketplace Tech team within the CSO organization—a highly visible group responsible for designing, building, and scaling solutions that free up data and empower business decisions across Fitch. The team collaborates closely with stakeholders across the organization to deliver next-generation data capabilities with a focus on faster time to market, data engineering, robust data controls, innovation, and leveraging AI/ML for data solutions.

How You’ll Make an Impact:

• Design, build, test, and deploy scalable data pipelines, APIs, and data products that support business, analytics, and AI-driven use cases.
• Act as a hands‑on technical lead, contributing directly to coding, SQL development, testing, troubleshooting, and production support while ensuring high-quality delivery.
• Develop robust solutions across data lakes, data warehouses, and governed data environments, with a strong focus on performance, reliability, scalability, and maintainability.
• Work on LLM-based developer tools, prompt‑enabled workflows, conversational search, RAG pipelines, vector databases, MCP-based integrations, or other tooling that supports intelligent automation and agentic use cases.
• Partner with business, analytics, and AI/ML teams to deliver data solutions aligned to enterprise priorities, including support for Agentic AI tools and platforms, intelligent automation, and AI‑ready data workflows.
• Lead technical design, delivery planning, and coordination across multiple initiatives, while mentoring junior engineers and promoting strong engineering, DevOps, and DataOps practices.
• Establish and enforce data engineering standards for code quality, testing, documentation, observability, and operational support to improve platform stability and delivery consistency.
• Drive continuous improvement of data architecture, pipeline efficiency, and reusable engineering patterns to enable faster delivery and better scalability across enterprise data initiatives.

You May be a Good Fit if:

• 5 – 8 years of hands‑on experience in data engineering or data platform development, ideally within financial services or another regulated industry.
• Expertise in SQL and Python, including experience building APIs, data pipelines, transformation frameworks, and production‑grade data solutions.
• Experience in designing and supporting solutions on AWS as the preferred cloud platform, with familiarity in similar cloud environments, and hands‑on experience with containerization, especially Kubernetes/EKS, as well as serverless services such as AWS Lambda and event‑driven architectures.
• Experience in working with Data Lakes, Data Warehouses, Data Governance, and Data Mesh concepts, along with modern engineering practices such as CI/CD, automated testing, Agile delivery.
• 1-2 years of AI-enabled engineering or data tooling, such as LLM‑based developer tools, prompt‑enabled workflows, semantic search, RAG p