We are looking for a chief-level Chief Data Engineer to own end-to-end data modeling and pipeline delivery for a multi-phase enterprise data lake re-architecture on a modern AWS stack. You will partner closely with stakeholders across time zones and drive outcomes with high autonomy. Apply now.ResponsibilitiesLead dimensional data modeling using star schemas, fact/dimension design, and aggregate-aware structuresOwn end-to-end pipeline delivery from requirements discovery through deployment and hypercareDesign ETL/ELT workflows that evolve traditional warehousing practices into a modern lakehouse approachBuild and maintain transformations in dbt with reliable tests, documentation, and lineage practicesDevelop data pipelines in Databricks with performance, scalability, and maintainability in mindPartner with US-based stakeholders to elicit requirements, clarify definitions, and anticipate future needsCoordinate delivery across an engineering team with time-zone overlap and ensure clear handoffsValidate data quality through SQL-based checks, unit tests, and UAT supportDocument models,



pipelines, and decisions to enable alignment and long-term maintainabilityProvide basic dashboarding support to validate outputs and confirm business usabilityRequirements7+ years of data engineering experience with modern data warehousing and lakehouse patterns7+ years of hands-on SQL experience for analytics engineering and data validationExperience with ETL/ELT solutions across batch and incremental processingExperience with Databricks in production environmentsExperience with dbt for transformations, testing, and documentationSenior stakeholder management experience working with non-technical partnersEnd-to-end delivery ownership from requirements through deployment and supportStrong dimensional modeling skills using star schema and Kimball methodologyStrong documentation skills using collaboration tools (e.g., Confluence)Excellent communication skills for clear written updates and ex

📌 Chief Data Engineer (México)
🏢 Epam Systems
📍 México