Databricks-PySpark
2 weeks ago
We are looking for a Senior Data Engineer with 6+ years of experience to design, build, and optimize scalable data solutions. The ideal candidate will have deep expertise in Databricks, Azure, Python, PySpark, Scala, ETL, and data governance. You will lead the development of efficient data pipelines and mentor junior engineers, ensuring operational excellence across data systems.
Key Responsibilities:
- Data Pipeline Development:
Design and implement batch and real-time ETL pipelines using Databricks, Azure Synapse, ADF, and other data platforms, working with both structured and unstructured data. - Leadership & Mentorship:
Advise and mentor teams on best practices for scalable data architectures, code quality, and CI/CD integration. Lead code and design reviews. - Advanced SQL & Platform Expertise:
Develop advanced SQL queries, stored procedures, and optimize Synapse and SQL Server environments for performance and scalability. - Collaboration & Problem Solving:
Partner with business analysts and solutions architects to deliver data solutions that align with business goals. Conduct root cause analysis to resolve data issues and improve processes. - Best Practices:
Ensure adherence to data governance standards, dimensional modeling, and efficient data warehousing practices. - Optional (Preferred):
Experience with Boomi for data integration.
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