AVP, Principal Data Engineer (L11)

Role Title : AVP, Principal Data Engineer (L11) Company Overview: Synchrony (NYSE: SYF) is a leading consumer financing company that has been at the heart of American commerce and opportunity for nearly a century. Synchrony delivers credit and banking products that empower tens of millions of consumers to improve their financial lives and access what matters most. Leveraging innovative solutions that are shaping the future of retail commerce, Synchrony supports the growth and success of some of the nation’s most respected brands, alongside hundreds of thousands of small and midsize businesses, including health and wellness providers. Committed to excellence in service and culture, Synchrony is proud to be named as #3 as a Great Place to Work® in India and is honored to be ranked the #1 Best Company to Work For® in the U.S. by Fortune magazine and Great Place to Work®. For more information, visit www.synchrony.com. Organizational Overview: Synchrony's Data Engineering team architects and operates cloud-native data platforms and event-driven pipelines that process hundreds of millions of credit card transactions annually, delivering curated, trustworthy datasets to downstream consumers and operational systems with high availability and strong reliability requirements We champion engineering rigor, data quality, and a platform-first mindset across  real-time event streaming, batch orchestration, Lakehouse architecture, and AI-ready data products, leveraging cutting-edge open-source and cloud-native technologies.

Summary/Purpose: We are looking for an AVP, Principal Data Engineer to serve as a hands-on technical leader who both drives and delivers, writing production-quality code, owning end-to-end data pipeline design and delivery, and setting the technical direction for the team. This role will lead the design and delivery of cloud-native, event-driven data platforms that power real-time transactional workflows and AI-ready data products, while modernizing legacy data systems and influencing architectural decisions across Synchrony’s enterprise data platform.

Design, develop, and lead production-grade data engineering applications across agile teams, combining hands-on coding with technical leadership, design reviews, and end-to-end delivery ownership. Design and implement scalable ELT/ETL and 24x7 real-time event streaming pipelines using Ab Initio Continuous Flows/Spark Streaming and Kafka ecosystems (AWS MSK and Confluent Kafka), ensuring fault tolerance, strong delivery guarantees (idempotency/exactly-once where applicable), and near-zero downtime deployments. Own event-driven data workflows that process high-throughput, low-latency financial transactions across mission-critical systems, and build/operate Lakehouse data infrastructure on AWS (S3, Glue, EMR, Redshift), using Ab Initio (must-have) and Spark as core engineering tool. Develop AI-ready data products and feature pipelines for downstream analytics and operational AI use cases, and lead cloud migration efforts to modernize legacy batch ETL into cloud-native, event-driven architecture. Collaborate with solution architects to translate designs into robust, scalable implementations; partner with product owners and program managers in a SAFe/Scaled Agile environment to align delivery with business priorities. Define and enforce data engineering standards, coding best practices, CI/CD, and DevOps processes; mentor engineers and foster a culture of engineering excellence and continuous learning. Required Skills/Knowledge : Bachelor’s degree in Computer Science, Engineering, or related field with 8+ years of experience in ELT/ETL, data warehousing, or Lakehouse engineering; or, in lieu of a degree with 10+ years of equivalent hands-on experience. 8+ years of full lifecycle data engineering experience (design, development, testing, documentation, performance tuning, and production support) across