01Overview
We are looking for an experienced Azure Databricks Engineer with robust hands-on expertise in Python, SQL, and Apache Spark to design, build, and optimize scalable data pipelines and analytics solutions on the Azure cloud platform. The ideal candidate should have experience working with large datasets, distributed data processing, and up-to-date data engineering practices.
Responsibilities
Design, develop, and maintain scalable data pipelines using Azure Databricks
Implement ETL/ELT workflows using PySpark, Spark SQL, and Python
Optimize Spark jobs for performance, cost, and scalability
Work with structured and semi-structured data (Parquet, Delta, JSON, CSV)
Build and manage Delta Lake tables (ACID, time travel, schema evolution)
Integrate Databricks with Azure Data Lake Storage (ADLS Gen2)
Develop complex queries and transformations using SQL
Collaborate with data scientists, analysts, and stakeholders to support analytics and ML use cases
Ensure data quality, validation, and monitoring
Follow best practices for security, access control, and governance in Azure Qualifications
6+ years of experience in Data Engineering
Robust hands-on experience with Azure Databricks
Proficiency in Python for data processing
Strong knowledge of SQL (joins, window functions, performance tuning)
Hands-on experience with Apache Spark / PySpark
Experience working with Delta Lake
Knowledge of Azure Data Lake Storage (ADLS Gen2)
Understanding of distributed computing concepts
Experience with Git version control
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying. .
