Data Support Engineer

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