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ILLUMEN GROUP INC - Data Support Engineer

Remote · USA Full-time New today
ILLUMEN GROUP INC - Data Support Engineer All Jobs > Data Support Engineer

ILLUMEN GROUP INC

Apply Data Support Engineer Fully Remote Apply Description

This role focuses on supporting data modernization and cloud migration efforts. The position centers on working with SQL-based systems, building and maintaining ETL pipelines, and helping transition legacy data environments into modern cloud-based architectures.

The ideal candidate has strong experience with database technologies such as PostgreSQL and Oracle, hands-on experience with data transformation and migration, and is comfortable working across both on-prem and cloud environments.

Key Responsibilities

  • Design, develop, and optimize SQL queries for performance and scalability
  • Build and maintain ETL pipelines for data ingestion, transformation, and migration
  • Support data modernization efforts, including legacy database re-engineering
  • Develop data solutions using Python or PySpark within AWS environments
  • Assist in migrating and transforming data across database platforms (e.g., Oracle to PostgreSQL)
  • Collaborate with stakeholders to improve data quality, accessibility, and performance
  • Support both cloud and on-prem data environments
  • Troubleshoot data-related issues and implement long-term solutions
Requirements

Qualifications

  • 3+ years of experience working with SQL (PostgreSQL, Oracle preferred)
  • 3+ years of experience building or maintaining ETL pipelines
  • Experience with data migration and transformation efforts
  • Experience working in AWS environments
  • Proficiency in Python or similar scripting language
  • Experience supporting both on-prem and cloud-based systems
  • Bachelor’s degree in Information Technology, Engineering, or related field (or equivalent experience)

Preferred

  • Experience with PySpark, Databricks, or similar data processing tools
  • Familiarity with AWS data services (S3, Glue, Redshift, Athena)
  • Experience with workflow orchestration tools (e.g., Airflow)
  • Exposure to data modeling and data lake architectures
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