We are looking for a Lead Data Engineer to build and evolve a next-generation analytics platform with a strong focus on Databricks and scalable data products. You will combine hands-on delivery with technical leadership across ingestion, modeling, governance, and AI-enabled engineering practices. Responsibilities Design scalable data ingestion, transformation, and data product frameworks Define Databricks best practices, including Medallion Architecture, optimization, governance, and operational standards Build batch, near real-time, and streaming pipelines using Databricks capabilities Deliver end-to-end data products that support analytics use cases across domains Develop trusted analytical datasets, semantic models, and governed consumption layers for reporting Implement data quality, lineage, monitoring, and observability practices across pipelines Enable self-service analytics through reusable,



business-ready datasets and platform features Lead proof-of-concepts and evaluate emerging capabilities across the Databricks ecosystem Define AI SDLC practices and AI-assisted development patterns to accelerate delivery Partner with engineering, analytics, product, and business stakeholders and mentor engineers on best practices Requirements5+ years of data engineering experience1+ years of technical leadership experience guiding engineering standards and best practices Strong platform delivery experience building enterprise analytics solutions end to end Advanced Apache Spark and Py Spark expertise for large-scale processing Strong Databricks production experience with performance optimization and operational excellence Advanced SQL skills for transformation, modeling, and analytics consumption Strong data governance knowledge including security, quality, and lineage practices Solid CI/CD experience and Data Engineering SDLC best practices Strong communication skills to lead technical discussions with cross-functional stakeholders Upper-Intermediate English proficiency

📌 Lead data engineer (México)
🏢 Epam Systems
📍 México