Assistant Vice President - Complaints Data Strategy, Architecture and

Synchrony; Hyderabad; On-site; INR 4,000,000 - 9,000,000; Full time

Job summary

Synchrony is seeking an AVP, Enterprise Complaints Data Strategy, Architecture & Governance to lead end‑to‑end data strategy for the complaints ecosystem. You will own target state, operating model, and multi‑quarter roadmaps across complaint systems and channels, architect scalable data models and domain aligned data products enabling analytics, governance reporting and issue management.

You will collaborate with Enterprise Complaints, Data Lake, and Governance leaders to prioritize

Qualifications

• 4 years' experience spanning data engineering, data architecture, and data governance/controls.
• Experience in regulated environments is preferred.
• Ownership of data strategy and end‑to‑end architecture for critical domains.

Responsibilities

• Define & execute the Enterprise Complaints Data Strategy and multi‑quarter roadmaps across platforms.
• Architect scalable data models and domain‑aligned data products for analytics and governance.
• Onboard new data sources, assess quality, lineage, and controls; manage data issues.
• Maintain Collibra assets, data dictionaries, and data quality dashboards.
• Collaborate with cross‑functional teams to drive adoption and data‑driven outcomes.

Skills

Data engineering

Data architecture

Data governance

Regulatory compliance

Data quality

Tools

Collibra

Tableau

PySpark

Scala Spark

SAS

Job description

AVP, Complaints Data Strategy, Architecture & Governance (L11) : Role Title : AVP, Complaints Data Strategy, Architecture & Governance (L11) Company Overview: Synchrony (NYSE: SYF) is a premier consumer financial services company delivering one of the industrys most complete digitally enabled product suites. Our experience, expertise and scale encompass a broad spectrum of industries including digital, health and wellness, retail, telecommunications, home, auto, outdoors, pet and more. We have recently been ranked #2 among Indias Best Companies to Work for by Great Place to Work.

We were among the Top 50 Indias Best Workplaces in Building a Culture of Innovation by All by GPTW and Top 25 among Best Workplaces in BFSI by GPTW. We have also been recognized by AmbitionBox Employee Choice Awards among the Top 20 Mid-Sized Companies, ranked #3 among Top Rated Companies for Women, and Top-Rated Financial Services Companies. We provide best-in-class employee benefits and programs that cater to work-life integration and overall well-being.

We provide career advancement and upskilling opportunities for all to take up leadership roles.

Organizational Overview: The Enterprise Complaint and Customer Experience function provides operational management, governance and reporting for the Companys complaint management procedures, ensuring consumer complaints are consistently identified across all intake channels and handled in accordance with internal policies and applicable regulatory requirements.

We turn complaint signals into action: spotting systemic journey breakdowns, partnering across the company to drive root‑cause fixes, and escalating emerging regulatory, financial, and reputational risks all while raising the bar on the customer experience.

Role Summary/Purpose: The AVP, Enterprise Complaints Data Strategy, Architecture & Governance is a senior, hands‑on leader responsible for defining and executing the end-to‑end data strategy for Synchronys enterprise complaints ecosystem. This role owns the target‑state vision, operating model, and multi‑quarter roadmap across complaint systems and channels, and architects scalable data models and domain‑aligned data products that enable complaint analytics, governance reporting, and issue management.

Key Responsibilities:

• Define & execute the Enterprise Complaints Data Strategy: Establish the target‑state vision, operating model, standards, and procedures; drive a multi‑quarter roadmap across complaint platforms and intake channels.
• Architect the complaints data ecosystem: Design and implement scalable data architectures, data models, and domain‑aligned data products that power analytics, governance reporting, and issue management.
• Assess and onboard new data sources: Build and execute repeatable approaches to evaluate new data sources (quality, completeness, lineage, controls), and recommend/implement optimal remediation paths to address data quality gaps. Ensure alignment to Enterprise Data Policy & Standards: Own and maintain Collibra assets (business definitions, lineage, retention, access controls), steward data dictionaries, and lead intake/resolution of data issues and incidents as the complaints data domain steward. Establish and run data quality controls & monitoring: Define data quality metrics, execute periodic data quality audits, and develop/maintain Tableau control and data operations dashboards to monitor health, surface emerging issues, and track KPIs across the complaints data environment.
• Drive cross-functional delivery and adoption: Partner across Enterprise Complaints and with Enterprise Data Lake, Technology, Data Office, Operations, and Governance leaders to prioritize initiatives, align dependencies, and ensure solutions are adopted and sustained.
• Enable advanced analytics and innovation: Deliver curated/aggregated datasets that support advanced analytics use cases including trend detection, anomaly detection, and thematic risk identification. Lead projects and mentor less experienced staff member s, and p erform special projects as assigned in support of enterprise complaint program maturity, platform modernization, and regulatory commitments.

Qualifications/Requirements:

4 years' experience spanning data engineering, data architecture, and data governance/controls, ideally in a regulated environment (financial services preferred) OR in lieu of a bachelor's degree, a minimum of 6 years of hands‑on data engineering & governance experience. Demonstrated ownership of data strategy and architecture for a business-critical domain (end‑to‑end from source to curated layers to consumption). 4 years Hands‑on Data Engineering experience building scalable pipelines and curated datasets using Pypark/ScalaSpark/SAS Demonstrated experience with design and conduct complex analysis on large structured , unstructured data to identify and remediate data quality or integrity issues Experience with automating and consolidating data from multiple .