PySpark Data Engineer

Role & Responsibilities

• Design, develop, and maintain scalable data pipelines using PySpark.
• Process and transform large volumes of structured and unstructured data.
• Develop ETL workflows and data integration solutions.
• Build and optimize Spark jobs for performance and scalability.
• Work with SQL, Spark SQL, and big data technologies.
• Ensure data quality, reliability, and operational excellence.
• Troubleshoot data processing and pipeline issues.
• Collaborate with business and technical stakeholders to deliver solutions.

Preferred Candidate Profile

• 2-5 years of experience in Data Engineering.
• Strong hands-on experience with PySpark and Apache Spark.
• Good coding skills in Python.
• Strong SQL and database knowledge.
• Experience in ETL, data integration, and big data projects.
• Exposure to Hadoop, Hive, or Databricks is preferred.
• Understanding of Data Warehousing concepts.
• Strong analytical and problem-solving skills.
• Good communication skills.