Senior Data Engineer - On-Prem & AWS Platform

Synchrony; Chicago (IL); Hybrid; USD 100,000 - 170,000; Full time

Job summary

Synchrony is seeking a Senior Data Engineer to lead data warehouse design, development, and migration to AWS (Redshift) while maintaining on‑prem solutions. You will guide a technical team, collaborate with product managers and architects, and ensure data platforms scale and stay highly available.

You will work within an agile environment, align with data governance, and promote automation across the data engineering function to support business goals.

Qualifications

• Bachelor's degree in technology or related field with at least 4 years of technology experience.
• Alternative: High School Diploma with at least 6 years in technology.
• Completion of Synchrony’s Business Leadership Program is a plus.

Responsibilities

• Understand and manage the data needs of stakeholders in a single business vertical.
• Design and implement scalable, fault-tolerant data applications on on-prem and AWS.
• Collaborate with information architects, platform architects, data scientists and product management to design solutions.
• Resolve problems through evaluation of business processes, system processes, enterprise standards & procedures.
• Comply with data management policies, standards and procedures.
• Lead the technical team to meet business goals and identify system enhancements.

Skills

ETL

Data warehousing

Cloud technologies (AWS)

Amazon Redshift

Ab Initio

SQL

DevOps

Scaled Agile

Stakeholder collaboration

Education

Bachelor's degree in technology or related field

High School Diploma/GED

Synchrony’s Business Leadership Program

Tools

On‑prem RDBMS platforms

Job description

Synchrony is seeking a Senior Data Engineer to lead data warehouse design, development, and migration to AWS (Redshift) while maintaining on‑prem solutions. You will guide a technical team, collaborate with product managers and architects, and ensure data platforms scale and stay highly available.

You will work within an agile environment, align with data governance, and promote automation across the data engineering function to support business goals.