Description

You will build, optimize, and maintain distributed data processing pipelines using Databricks, Spark, and Delta Lake on AWS.

This role is on-site.

Responsibilities

• Build and optimize distributed data processing jobs using PySpark and Scala.
• Implement data ingestion from structured and unstructured sources into S3 and Delta Lake.
• Deploy Databricks solutions into production alongside architects.
• Debug, optimize, and tune Spark jobs for performance.
• Participate in code reviews, testing, and CI/CD deployments.

Required Skills

• 7+ years of data engineering experience.
• Strong Databricks and Spark programming expertise.
• Hands-on AWS cloud experience (S3, Glue Catalog, Lambda, SNS/SQS, Redshift).
• Experience using Delta Lake, notebooks, workflows, and job clusters.
• Proficiency in PySpark and Spark.
• Familiarity with Git and CI/CD automation tools.
• Knowledge of Data Pipelines and ETL principles.

Key Skills

Education

Any Gradute