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Job Description
Structured overview of role & requirementsAbout This Role
Design, develop, and maintain scalable data pipelines and analytics solutions on the Azure cloud using Databricks.
Implement and optimize ETL/ELT workflows with PySpark, Spark SQL, and Python, focusing on performance, cost, and scalability.
Collaborate across teams to support analytics and machine learning use cases while ensuring data quality, security, and governance.
Minimum Requirements
6+ years of experience in Data Engineering.
Strong hands-on experience with Azure Databricks, Python, SQL, and Apache Spark/PySpark.
Experience with Delta Lake and Azure Data Lake Storage Gen2 (ADLS Gen2).
Familiarity with Azure Data Factory, Git version control, and cloud security including Role-Based Access Control (RBAC).
Ideal Candidate Profile
Experienced in designing scalable data pipelines on Azure with deep expertise in Databricks and distributed computing.
Skilled in performance tuning Spark jobs and managing complex data workflows involving structured and semi-structured data formats.
Capable of integrating DevOps practices such as CI/CD pipelines (Azure DevOps, GitHub Actions) and working within secure, governed Azure cloud environments.