Engineering & Quality - Software Engineer

This job is with Fitch Group, an inclusive employer and a member of my Gwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly.

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.

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

Visit:  (Usted puede enviar una solicitud o contactar con nosotros por email usando el Buzón de Solicitud online de abajo)/

How You’ll Make an Impact:

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 a 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.

You May be a Good Fit if:

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 virtualizations 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., Git Hub 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 data stores

Design applications with microservices and containerization mindset with ‘decoupling’ architectural principles

Caching with Valkey/Redis: TTL strategies, invalidation, key design.

CI/CD and IaC with Git Hub,…