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 applications for AI.
- Strong hands-on experience in generating semantic layers for the data products that serve multiple consuming applications on AWS.
- Proven experience building data pipelines for AI/ML use cases including ETL/ELT workflows, streaming data integration, and data preparation for model training and fine-tuning.
- Strong experience with Lakehouse architecture using S3, Apache Iceberg, Glue Data Catalog, Redshift
- Strong Python skills for building data processing, evaluation, and automation pipelines, plus familiarity with DevOps practices (CI/CD, infrastructure as code, environment management).
- Good understanding of identity and data security architecture - IAM, IAM Identity Center, cross account data access patterns, identity propagation for AI agents and services
Good understanding of AWS infrastructure concepts (networking, security, storage, compute) and how they- to data and AI workloads.
- Experience working with ETL/ELT pipelines, streaming data, and integration technologies (e.g., CDC, APIs, event buses) for both batch and real-time use cases.
- Proven ability to lead multi-disciplinary teams and influence across platform, AI, data, and business stakeholders.
Desired Skills/ Knowledge:
- Experience implementing or leveraging knowledge graphs, entity resolution, or semantic search to power AI and RAG use cases.
- Solid understanding of LLM and agentic AI patterns (prompts, tools, RAG, memory) and how data quality and structure impact AI behavior and performance.
- Background in building data products specifically targeted for AI/ML (feature stores, labeled datasets, evaluation datasets, fine-tuning corpora).
Familiarity with enterprise architecture frameworks (TOGAF) as they- to data and AI.
- Prior experience in financial services, credit, payments, or similar domains where data lineage, explainability, and audit trails are critical.
- Basic AWS solution architecture knowledge including core services, AWS S3, Redshift, Amazon Bedrock, and Bedrock AgentCore so they can collaborate effectively with platform and agent teams.
- Good understanding of enterprise data governance and access controls like AWS Lake Formation, Glue Data catalog and metadata management frameworks.
- Team player, strong engagement, positive attitude and natural curiosity are highly desired.
Eligibility Criteria :
- Bachelor's degree in Computer Science, Engineering, Information Systems, or related field (or equivalent experience).
- 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 familiarity with streaming through Kafka and other Data Lake technologies and techniques.
- Strong familiarity with data governance, data lineage, data processes, DML, and data architecture control execution
- Strong experience with business analysis - Requirements analysis and conversion to data models.
- Must be able to develop creative solutions to problems.
Work Timings: 2:00 PM to 11:00 PM IST
This role qualifies for Enhanced Flexibility offered in Synchrony India and will require the incumbent to be available between 06:00 AM Eastern Time – 11:30 AM Eastern Time (timings are anchored to US Eastern hours and will adjust twice a year locally). This window is for meetings with India and US teams. The remaining hours will be flexible for the employee to choose. Exceptions may periodically due to business needs) We are proud to offer flexibility at Synchrony. Our way of working allows you the option to work from home or workspaces in our Regional Engagement Hubs—Hyderabad, Bengaluru, Pune, Kolkata, or Delhi/NCR. Occasionally you may be required to commute or travel to Hyderabad or one of the Regional Engagement Hubs for in person engagement activities such as business or team meetings, trainings, and culture events.
For Internal Applicants:
Understand the criteria or mandatory skills required for the role, before
- ing
Inform your manager and HRM before - ing for any role on Workday
- Ensure that your professional profile is updated (fields such as education, prior experience, other skills) and it is mandatory to upload your updated resume (Word or PDF format)
- Must not be any corrective action plan (First Formal/Final Formal, LPP)
- L09 Employees who have completed 18 months in the organization and 12 months in current role and level are only eligible.
- L09+ Employees can
Level / Grade : 11
Job Family Group:
Information Technology
