Description

Experience Required: Minimum 10 Years

Responsibilities:

• Experience with big data processing and distributed computing systems like Spark.
• Implement ETL pipelines and data transformation processes.
• Ensure data quality and integrity in all data processing workflows.
• Troubleshoot and resolve issues related to PySpark applications and workflows.
• Understand source, dependencies and data flow from converted PySpark code.
• Strong programming skills in Python and SQL.
• Experience with big data technologies like Hadoop, Hive, and Kafka.
• Understanding of data warehousing concepts and relational databases like SQL.
• Demonstrate and document code lineage.
• Integrate PySpark code with frameworks such as Ingestion Framework, DataLens, etc.,
• Ensure compliance with data security, privacy regulations, and organizational standards.
• Knowledge of CI/CD pipelines and DevOps practices.
• Strong problem-solving and analytical skills.
• Excellent communication and leadership abilities.

Qualifications:

• 4+ years of experience in big data development, Hadoop, Hive & Spark framework.
• Good to have experience in SAS.
• Strong Python, PySpark Development and SQL knowledge.
• Certification in big data or cloud technologies is preferred.
• Excellent communication, collaboration, and problem-solving skills

Key Skills

Education

Any Graduate