Our client is seeking a Data Engineer based in Monterrey, Mexico. The team builds and maintains data pipelines, ETL processes, and data infrastructure supporting global financial data products.
As a leading, global financial information services provider, our client 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, our client's culture of credibility, independence, and transparency is embedded throughout its structure, which includes our client Ratings, one of the world's top three credit ratings agencies, and our client Solutions, a leading provider of insights, data and analytics. With dual headquarters in London and New York, our client is owned by Hearst.
Our client'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. Contribute as a member of a high-performing data engineering team by implementing modern, scalable data solutions aligned with business priorities.
Partner with the CDO team and data product leaders to implement the vision for an AWS-based data platform that enables enterprise-wide self-service, unlocking data for AI, analytics, and innovation.
Implement 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.
3-5 years' experience 'hands‐on' as a member of a highly technical data‐centric software engineering team, 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, RDS/Aurora, Valkey/Redis, Step Functions, MSK/Kafka, Event Bridge).
~ AWS Certification strongly preferred.
~ Git Hub Copilot, Amazon Q).
~ Strong Python for data engineering (Pandas, Spark/Py Spark) and API Development (Fast API or similar).
~ Design and build high‐performance REST/Graph QL 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.
~ Caching with Valkey/Redis: TTL strategies, invalidation, key design.
~ CI/CD and Ia C with Git Hub, Git/Git Hub workflows, Argo CD.
~ IAM, KMS, secrets, VPC networking, observability (Open Telemetry), SLOs, cost governance.
~ Ability to solve complex data‐driven requirements and triage towards defects and production bugs.
~ Technology solutions and tools, including data governance and catalog solutions (e.g., Collibra, Alation, data platform and lake(house) (i.e., medallion's architecture), and data mesh and virtualization tools (e.g., using Lang Chain or Llama Index), implementing RAG over enterprise data, and enforcing robust guardrails through rigorous testing and evaluation.
Git Hub Copilot, Amazon Q) and using agentic AI to automate workflows such as code reviews, test generation, data quality checks, and runbook execution.
Caching with Valkey/Redis: TTL strategies, invalidation, key design.
Work‐Life Balance First: 40% in‐office monthly stay connected while keeping flexibility.
Dedicated training, leadership development, and mentorship programs designed to ensure that your time at our client will be a continuous learning opportunity.
Retirement planning and tuition reimbursement programs that empower you to achieve your short and long‐term goals.
Promoting Health & Well‐being: Comprehensive healthcare offerings that enable physical, mental, financial, social, and occupational well‐being.
Supportive Parenting Policies: Family‐friendly policies, including a generous global parental leave plan, are designed to help you balance career and family life effectively.
Our client is committed to providing global securities markets with objective, timely, independent, and forward‐looking credit opinions. If you, or your immediate family, have any holdings that may conflict with your work responsibilities, you may be asked to divest yourself of them before beginning work.
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.
#
Sign in
To continue your applicationor continue with email
By continuing you agree to our Terms & Privacy Policy.
