- design, develop, test, and maintain scalable data pipelines and data products supporting enterprise credit risk initiatives.
- build and optimize batch and real-time data processing solutions using modern cloud and lakehouse technologies.
- partner with risk, product, data science, and engineering teams to understand business requirements and translate them into technical solutions.
- develop reusable frameworks, components, and engineering patterns that improve development efficiency and platform consistency.
- implement data quality controls, monitoring, alerting, and observability capabilities to ensure data reliability and trustworthiness.
- support the migration and modernization of existing data assets and workloads into databricks and cloud-native platforms.
- build and maintain curated datasets that support lending decisioning, portfolio risk management, and advanced analytics use cases.
- participate in architecture discussions and contribute technical recommendations for platform enhancements.
- troubleshoot production issues and drive root cause analysis to improve platform reliability and performance.
- follow engineering best practices for code quality, testing, deployment automation, security, and operational excellence.
- mentor junior engineers through code reviews, technical guidance, and knowledge sharing.




- continuously evaluate opportunities to improve scalability, performance, cost efficiency, and maintainability of data platforms.

qualifications

- strong experience developing and maintaining enterprise-scale data engineering solutions.
- hands‑on experience with databricks, apache spark, pyspark, hadoop, sql, and python.
- experience building etl/elt pipelines and large-scale data processing applications.
- experience working with cloud-based data platforms and storage technologies.
- strong understanding of data modeling concepts and analytical data structures.
- experience implementing automated testing, monitoring, and data quality practices.
- experience with data formats (parquet, avro, orc).
- knowledge of ci/cd pipelines, git‑based development workflows, and devops principles.
- experience with workflow orchestration tools like airflow.
- strong analytical and problem-solving skills with the ability to work independently on complex technical challenges.
- effective communication skills with the ability to collaborate across technical and business teams.
- experience mentoring or supporting less experienced engineers.
- knowledge of java based application development is a huge plus.

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📌 Data engineer (Jalisco)
🏢 HCLTech
📍 Jalisco