Our client is seeking a highly skilled Data Engineer with a strong background in building scalable data pipelines, performing complex data transformations, and enabling analytics workloads. The ideal candidate should have hands-on experience with Databricks on AWS, PySpark, and Python, with a working understanding of ETL orchestration and automation. Familiarity with Informatica DEI is a plus, as the role may involve refactoring existing Informatica workflows into PySpark.

Key Responsibilities:

• Design and implement robust, scalable data pipelines using Databricks on AWS and

PySpark

• Perform data ingestion, transformation, cleansing, and validation from various sources

• Collaborate with analytics and data science teams to deliver high-quality data for

reporting and modeling

• Understand and translate Informatica DEI workflows into Databricks-based

implementations (if applicable)

• Optimize and automate ETL workflows for performance and cost-efficiency

• Ensure data quality, lineage, and governance are upheld in all solutions

Required Skills & Experience:

• Minimum 8 years of overall experience with atleast 3 years in Data Engineering

• Strong proficiency in Databricks on AWS, PySpark, and Python

• Solid experience in ETL development, data transformations, cleaning, data quality

frameworks/standards, and pipeline automation

• Understanding of data quality principles and performance tuning techniques

• Familiarity with Informatica DEI is a nice to have

• Excellent communication skills in client-facing environments