Data Engineer (PySpark)

Role: Data Engineer

Location: Pune (On-site)

Job Type: Full-Time

Experience: 47 Years

Key Responsibilities

• Design, develop, and maintain scalable

  data pipelines

  and ETL workflows.
• Work with large datasets using

  PySpark

  ,

  Python

  , and

  SQL

  to ensure efficient data transformation and integration.
• Implement data solutions on

  AWS,

  leveraging services like S3, Glue, Lambda, and Redshift.
• Collaborate with cross-functional teams to define data requirements and optimize data flows.
• Work within

  Databricks

  to develop and deploy data engineering solutions.
• Ensure data quality, reliability, and security across all environments.
• Monitor and optimize data processes for performance and cost efficiency.

Required Skills

• Strong experience in

  Python

  ,

  PySpark

  , and

  SQL

  .
• Hands-on experience with

  AWS data services

  (Glue, Redshift, Lambda, S3, etc.).
• Expertise in the

  Databricks

  platform and data pipeline orchestration.
• Solid understanding of

  data warehousing

  ,

  data modeling

  , and

  ETL design principles

  .
• Excellent problem-solving skills and ability to work in a fast-paced environment.

Good to Have

• Exposure to the

  Fintech domain

  and understanding of financial data structures.
• Experience with CI/CD, Airflow, or other workflow orchestration tools.
• Familiarity with data governance and compliance best practices.