Description

Job Responsibilities include:

Design, develop, and deploy scalable ETL/ELT pipelines using Databricks, Apache Spark, and PySpark.

Optimize SQL queries and data transformations to improve performance, scalability, and efficiency.

Collaborate with data architects, analysts, and business teams to build data models and deliver insights.

Ensure data quality, reliability, and monitoring across all data pipelines and workflows.

Implement and manage CI/CD pipelines for Databricks jobs, notebooks, and deployments.

Provide production support, troubleshoot issues, and continuously enhance data engineering processes.

Required Qualifications:

Bachelor’s or master’s degree in computer science, Data Engineering, or a related field.

10–12+ years of experience in data engineering with 3–5 years of hands-on Databricks and Spark experience.

Strong expertise in Databricks, Apache Spark (PySpark/Scala), and SQL for building scalable ETL/ELT pipelines and data solutions.

Proven experience in Azure-based data platforms, data modeling, performance tuning, and implementing CI/CD workflows for data engineering

Key Skills

Education

Any Graduate