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

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  (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.