AVP, Complaints Data Strategy, Architecture & Governance

Role Overview

• 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 members, and perform special projects as assigned in support of enterprise complaint program maturity, platform modernization, and regulatory commitments.

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 reporting channels ensuring sound data quality controls and checks
• Strong project management, communications, multi-tasking, ability to work independently, relationship management skills are keys to success

Tech Stack

• Tableau

Benefits

• best-in-class employee benefits and programs that cater to work-life integration and overall well-being
• career advancement and upskilling opportunities for all to take up leadership roles