Lead Data Engineer with Databricks

hace 1 semana


distrito federal, México W3Global A tiempo completo

Must Design, build, and maintain scalable and efficient ETL/ELT data pipelines using Azure Data Factory and Azure Databricks. Write complex, high-performance SQL queries and scripts for data extraction, transformation, and loading. Implement data transformation logic using Python and PySpark (or Scala) within the Databricks environment. Hands‑on experience with Snowflake. Ensure pipeline reliability, scalability, and performance through monitoring, alerting, and proactive maintenance. Collaborate closely with data architects, analysts, and business stakeholders to understand data requirements and deliver actionable solutions. Enforce data governance and security best practices, ensuring compliance with organizational and regulatory standards. Optimize data storage, compute, and processing resources in the Azure ecosystem to reduce costs and improve efficiency. Document data flows, processes, and technical designs clearly and effectively. Contribute to code reviews, technical discussions, and mentorship of junior engineers. Bachelor's degree in computer science, Engineering, Information Systems, or a related technical field. 10 to 15 years of professional experience as a Senior Data Engineer. Strong hands‑on experience with Azure Data Factory and Azure Databricks. Proficiency in Python and SQL for data processing and scripting. Working experience with PySpark and/or Scala in distributed data processing. Solid understanding of ETL/ELT methodologies and best practices. Experience designing and managing data solutions in a cloud environment (Azure preferred). Proficient knowledge in Data Modeling and Data Warehousing. Expertise in DevOps processes. #J-18808-Ljbffr


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