Data Engineer

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, Airflow, etc.)

Preferred Background:

• Former Client contractors or employees with strong manager feedback
• Experience supporting financial services or large enterprise data initiatives
• Excellent communication and collaboration skills across technical and business teams