Job Summary:

We are seeking a highly skilled and experienced Senior ETL Developer with strong expertise in PySpark, Python, along with a solid background in ETL (Extract, Transform, Load) processes across relational databases and cloud platforms. The ideal candidate will have a minimum of 5 years of hands-on experience developing scalable data pipelines and ETL workflows using modern tools and frameworks.

Responsibilities:

Design, develop, and maintain ETL pipelines using PySpark and Python for large-scale data processing.
Implement validation logic as part of ETL workflows.
Work with relational databases (e.g., Oracle, PostgreSQL, SQL Server) to extract, transform, and load data efficiently.
Develop and optimize data pipelines on cloud platforms (AWS) using Spark-based frameworks (Data Frames).
Collaborate with data architects, analysts, and other stakeholders to understand requirements and deliver reliable data solutions.
Ensure data integrity, performance, and quality in all ETL processes.
Participate in code reviews, testing, and deployment of data solutions.

Required Qualifications:

5+ years of experience in ETL development with a strong foundation in data integration, transformation, and loading.
Proven experience writing efficient code in PySpark and Python, especially for large-scale data sets.
Hands-on experience with creating ETL workflows.
Strong experience working with relational databases and writing complex SQL queries.
Solid understanding of data modeling, performance tuning, and best practices in ETL design.
Experience with cloud-based data processing using Spark on AWS.
Strong communication and collaboration skills.

Preferred Qualifications:

Experience with data orchestration tools like Apache Airflow or similar.
Familiarity with data governance and security best practices.
Experience in Agile/Scrum environments.

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ETL Developer

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