Engineering & Quality - Software Engineer Requisition ID: 49925 Business Unit: Fitch Group Category: Information Technology Location: Monterrey, MX Date Posted: May 6, 2026 Fitch Group is currently seeking a Data Engineer based out of our Monterrey, 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. Responsibilities Hands-On Lead and mentor a high-performing data engineering team, fostering technical excellence and professional growth while ensuring delivery of scalable, modern data solutions aligned with business priorities. Partner with the CDO team and data product leaders to define and execute the vision for an AWS-based data platform that enables enterprise-wide self-service, unlocking data for AI, analytics, and innovation. Drive architectural decisions and establish best practices for data ingestion, transformation, and distribution frameworks that accelerate time-to-insight for data producers and consumers. Champion adoption of emerging technologies such as Agentic AI and Generative AI, integrating advanced capabilities into data workflows to enhance user experience and position the organization as “AI-Ready.” Ensure operational excellence and reliability by proactively addressing complex data engineering challenges, implementing robust quality controls, and preventing production incidents. Qualifications 4 to 5 years’ experience hands-on leading highly technical data-centric software engineers, preferably in financial services, in support of Data Lake houses (e.g. AWS, Databricks, Snowflake), data virtualization solutions (e.g. Starburst), modern data catalogs & data quality capabilities (e.g. Collibra), and Master Data Management (e.g. Informatica). Proven AWS expertise (S3, EKS, Lambda, Glue, EMR, Redshift, S3, RDS/Aurora, Valkey/Redis, Step Functions, MSK/Kafka, Event Bridge). AWS Certification strongly preferred. Experience applying AI/ML to boost engineering productivity (e.g., GitHub Copilot, Amazon Q). Strong Python for data engineering (Pandas, Spark/PySpark) and API development (FastAPI or similar). Design and build high-performance REST/GraphQL APIs with optimized query patterns, pagination, caching, and schema design to ensure low-latency, performant reads at scale. Build ETL/ELT pipelines for batch and streaming; Kafka/MSK with schemas (Avro/JSON) and delivery semantics. Optimize performance of object-based and relational datastores. Design applications with microservices and containerization mindset with decoupling architectural principles. Caching with Redis: TTL strategies, invalidation, key design. CI/CD and IaC with GitHub, Git/GitHub workflows, ArgoCD. Security and reliability: IAM, KMS, secrets, VPC networking, observability (OpenTelemetry), SLOs, cost governance. Ability to solve complex data-driven requirements and triage towards defects and production bugs. Experience with data governance and catalog solutions (e.g. Collibra, Alation), data platform and lakehouse architectures, data mesh and virtualization tools (e.g. Starburst, Denodo). Experience in leading evaluation of new technologies and methodologies to enhance efficiency (Buy vs Build). What Would Make You Stand Out Hands-on experience building AI agents (e.g., LangGraph or LlamaIndex), implementing RAG over enterprise data, and enforcing robust guardrails through rigorous testing and evaluation, including Agentic AI connection protocols (e.g., MCP, A2A). Applying AI/ML to boost engineering productivity (e.g., GitHub Copilot, Amazon Q) and using agentic AI to automate workflows such as code reviews, test generation, data quality checks, and runbook execution. Knowledge on SSO implementation and Azure AD (MS Entra) groups. Great communication and collaboration skills. Proven ability to drive innovation and install a culture of continuous improvement that measurably improves business outcomes. Ability to communicate effectively and translate technical concepts to senior management and non-technical stakeholders. Equal Opportunity Fitch is proud to be an Equal Opportunity and Affirmative Action Employer. We evaluate qualified applicants without regard to race, color, national origin, religion, sex, sexual orientation, gender identity, disability, protected veteran status, and other statuses protected by law. #J-18808-Ljbffr