PySpark Developer – ETL & SQL

Develop and maintain robust data pipelines using PySpark .

Design and build scalable ETL processes to support business and analytics needs.

Write optimized SQL queries for data extraction, transformation, validation, and reporting.

Work with large volumes of structured and unstructured data.

Ensure data quality, accuracy, and consistency across various data sources.

Identify and resolve performance bottlenecks in existing data workflows.

Collaborate with cross-functional teams to understand requirements and deliver reliable data solutions.

Participate in code reviews and contribute to data engineering best practices.

4–8 years of experience in Data Engineering or related roles.

Strong hands-on experience with PySpark and large-scale data processing.

Solid expertise in designing and developing ETL pipelines .

Advanced SQL skills, including query optimization and performance tuning.

Good understanding of data warehousing and data modeling concepts.

Strong problem-solving skills and attention to detail.

Excellent communication and collaboration skills.

Experience with AWS.

Exposure to Airflow or other workflow orchestration tools.

Familiarity with Hadoop ecosystem technologies.

Experience working with modern data lake or cloud data platforms.