Description

You build and maintain data pipelines to move and transform data into AWS environments.

Responsibilities

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

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.
  • Bachelor's degree in Computer Science, MIS, or related field.

Education

Bachelor's degree