Description

You design, build, and optimize ETL pipelines and scalable data solutions. This role is on-site.

Responsibilities

• Design and optimize ETL pipelines using Python, PySpark, and Spark.
• Develop scalable data solutions leveraging Databricks, AWS Glue, EMR, and S3.
• Collaborate with engineering and analytics teams on data ingestion, transformation, and storage.
• Support data quality, performance tuning, and process automation across the data lifecycle.
• Work in Agile environments utilizing CI/CD and version control tools.

Required Skills

• 7+ years of experience in data engineering, preferably in cloud 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 including Git, Jenkins, Terraform, and Airflow.

Preferred Skills

• Experience with Redshift and Athena for data warehousing and querying.
• Background in Agile development methodologies.

Key Skills

Education

Any Gradute