Description

Build and maintain data pipelines to move and transform data into AWS environments.

This role is hybrid.

Responsibilities

• Develop and maintain ETL/ELT pipelines extracting data from Oracle and other systems into AWS (S3, Redshift, Glue).
• Implement and manage data ingestion frameworks covering both batch and streaming requirements.
• Automate and schedule data workflows using AWS Glue, Step Functions, or Airflow.
• Collaborate with data scientists to prepare and optimize data for SageMaker workloads.
• Design and maintain data models, schemas, and cataloging processes for consistency.

Required Skills

• 5+ years of experience in a data engineering role.
• Strong proficiency with SQL and hands-on experience with Oracle databases.
• Proficiency in Python, including pandas, boto3, and pyodbc.
• Hands-on experience with AWS data services: S3, Glue, Redshift, Lambda, and IAM.
• Solid understanding of data modeling, relational databases, and schema design.
• Experience designing and implementing ETL/ELT pipelines and data workflows.
• Familiarity with version control, CI/CD, and automation practices.

Preferred Skills

• Experience optimizing data processes for performance and cost efficiency.
• Knowledge of Java or MLOps practices.

Key Skills

Education

Bachelor's degree