Description

Job Responsibilities include:

Design, develop, and deploy scalable ETL/ELT pipelines using Databricks, Apache Spark, and PySpark to support enterprise data initiatives.

Build and optimize SQL-based data transformation processes, data models, and analytics solutions for performance and scalability.

Develop and maintain Delta Lake architecture and enterprise data pipelines on Azure cloud platforms.

Implement data quality controls, workflow orchestration, operational monitoring, and production support processes to ensure reliable data delivery.

Collaborate with data architects, business analysts, product owners, and stakeholders to translate business requirements into technical solutions.

Manage CI/CD processes for Databricks notebooks, jobs, and workflows while continuously improving platform performance, reliability, and efficiency.

Required Qualifications:

Bachelor’s degree in computer science, Information Technology, Data Engineering, Software Engineering, or a related field.

4–6 years of experience in Data Engineering, ETL/ELT development, or cloud-based data platforms.

Strong hands-on experience with Databricks, Apache Spark, SQL, and ETL/ELT pipeline development in Azure environments.

Proficiency in Python or Scala, along with experience in data modeling, performance tuning, production support, and operational monitoring

Key Skills

Education

Any Graduate