Job Description

Job Description

:


Key Responsibilities:
  • Design, build, and optimize ETL pipelines using Python, PySpark, and Spark
  • Develop scalable data solutions leveraging Databricks, AWS Glue, EMR, and S3
  • Collaborate with cross-functional engineering and analytics teams to implement best practices in data ingestion, transformation, and storage
  • Support data quality, performance tuning, and process automation across the data lifecycle
  • Work in Agile environments with CI/CD and version control tools
    • Required Skills and Experience:
  • 3 to 7 plus years of experience in data engineering, preferably in cloud-based environments
  • Strong proficiency in Python, PySpark, Spark, and SQL
  • Hands-on experience with AWS data services (S3, Glue, EMR, Redshift, Lambda, Athena)
  • Experience with Databricks or equivalent data lake platforms
  • Familiarity with modern DevOps practices (Git, Jenkins, Terraform, A...

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