We are looking for a talented PySpark Data Engineer with 2-5 years of experience in developing scalable data processing and ETL solutions. The ideal candidate should have strong expertise in PySpark, Python, SQL, and big data technologies.

Role & Responsibilities

Develop and maintain scalable data pipelines using PySpark.
Process and transform large volumes of structured and unstructured data.
Design and implement ETL workflows and data integration solutions.
Optimize Spark applications for performance and scalability.
Work closely with business and technical teams to deliver data solutions.
Ensure data quality, reliability, and operational excellence.
Troubleshoot and resolve issues related to data processing workflows.
Follow best practices for data engineering and software development.

Preferred Candidate Profile

2-5 years of experience in Data Engineering.
Strong hands-on experience in PySpark and Apache Spark.
Good programming skills in Python.
Strong SQL and database concepts.
Experience in ETL development and data integration.
Understanding of Big Data technologies.
Knowledge of Hadoop, Hive, or Databricks is an added advantage.
Strong analytical, problem-solving, and communication skills.

PySpark Data Engineer

Job Description

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