AVP, Data Architect (L11)

Job description

Role Title: AVP, Data Architect (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 Engineering Team is a dynamic and innovative team dedicated to driving technological excellence. As a member of this Team, you'll play a pivotal role in designing and developing cutting-edge tech stack and solutions that redefine industry standards. The Credit Card that we use every day to purchase our essentials and later settle the bills - A simple process that we all are used to on a day to day basis. Now, consider the vast complexity hidden behind this seemingly simple process, operating tirelessly for millions of cardholders. The sheer volume of data processed is mind-boggling. Fortunately, advanced technology stands ready to automate and manage this constant torrent of information, ensuring smooth transactions around the clock, 365 days a year. Our collaborative environment encourages creative problem-solving and fosters career growth. Join us to work on diverse projects, from fintech to data analytics, and contribute to shaping the future of technology. If you're passionate about engineering and innovation. Role Summary/Purpose The AVP, Data Architect owns how data is sourced, modeled, governed, and delivered for analytic workloads, reporting/dashboarding and agentic AI solutions. The Data Architect will need to develop intimate knowledge of SYF key data domains (originations, loan activity, collection, etc.) and maintain a holistic view across SYF functions to design performant, resilient and cost-effective data solutions. This role requires strong hands-on experience for preparing data for AI data pipelines so agents can reliably access high-quality, compliant information. The role partners closely with the data engineering team, AI Platform team, the data governance team, data science/analytics teams, and business stakeholder teams to define data architecture, standards, and operating models that enable scalable, secure, and cost-effective analytics and AI workloads. This leader combines deep data architecture skills, strong understanding of different data model methodology, ETL pipelines, AI/LLM/RAG patterns. Key Responsibilities • Define logical, physical data model structure, integrate, govern, and store data in the enterprise repositories for supporting analytics/data science workloads, reporting/dashboarding and agentic AI workloads. • Execute POCs and prototypes in sandbox and lab environments to propose solutions for AWS cloud workloads and AI solutions using data on AWS. • Document data flow diagrams. Ensure discipline in the creation of Logical Data Models and their later implementation as Physical Data Structures. • Define the target-state Data & AI Foundations architecture supporting agentic AI use cases, enterprise knowledge graph or metadata layer, data products, and AI-ready datasets. • Assist in developing the strategy and roadmap for making key enterprise data sources "AI-ready": curation, quality, metadata, access patterns, latency requirements, and retention. • Partner with source system owners (core servicing, CRM, collections, risk, fraud, etc.) to define data contracts, SLAs, and integration patterns that support downstream analytics. • Establish data preparation and curation pipelines for model fine-tuning, including dataset selection, labeling strategies, quality validation, versioning, and compliance with model risk policies. • Define and enforce data governance policies for AI: data classification, lineage, access controls, PII handling, retention, and usage logging for AI workloads. • Partner with AI Governance/Model Risk and InfoSec/AppSec to ensure data usage in prompts, context, and tools adheres to policies, including regulatory, privacy, and model risk requirements. • Establish data quality and observability practices for AI data: data SLAs, freshness, completeness, drift detection, and business rule validation tied to AI outcomes. • Drive adoption of metadata and catalog tools so platform and agent teams can discover, understand, and safely consume datasets. • Define and oversee patterns for integrating external data (third-party, public, partner data) into AI workflows, including licensing checks, quality assessment, and monitoring. • Perform other duties and/or special projects as assigned. Qualifications/Requirements • Minimum 6+ years of experience across data engineering, data architecture, or analytics platforms, with at least 3+ years in cloud data platforms and enterprise data leadership roles. • Strong experience with modern cloud data stacks (e.g., data warehouses like Redshift/Snowflake/BigQuery, relational databases like PostgreSQL, and object storage) and their use in analytics and AI. • Demonstrated expertise in enabling data readiness for agentic AI from existing data stores in front-end (OLTP) applications or analytical (OLAP) applications like data lake and warehouses. Strong hands-on experience on designing data models (star schema, 3NF) for raw, standardized and curated data products for optimal performance and scalability of data