Job Description

Core Responsibilities

• Own technical product managementfor master dataproducts, with end-to-end accountability across the data lifecycle:ingestion, transformation, modeling, orchestration, storage, and consumption Actively contributesto solution design and continuous technical improvement.

• Lead crossfunctional collaborationwith data engineering, BI/analytics engineering,infrastructure, governance, and business teams to define and operationalize best practices formaster data management (MDM), reference data management (RDM), data modeling, data quality frameworks, and data contracts

• Apply handson SQLproficiencyto explore datasets,validaterequirements, assess data quality, and independently analyze issues and trends that inform prioritization, roadmap decisions, and stakeholder conversations.

• Translate business needs into executable data product requirements, includinghierarchies, schemas, transformations,dataquality rules, SLAs, and downstream consumption patterns

• Coach and guide delivery teamson data product best practices—backlog structure, dependency management, technical tradeoff analysis, and outcome

• based planning—while ensuring clear, consistent communication for data producers and consumers.

• Partner with engineering and stakeholders to resolve production issues, including data quality defects, pipeline failures, orchestration errors, and downstream analytics breakages. Drivequerylevel investigation, rootcause analysis, and sustainable remediation.

• Support the launch and adoptionof master and reference data products by improving usability, trust, and consistency across operational systems, analytics, and reporting use cases.

• Use quantitative analysis and data profilingto continuously improve data accuracy, completeness, consistency, and timeliness, balancing governance requirements with usability and speed.

• Influence roadmap and prioritization decisionsbyrepresentingdata quality risk, architectural dependencies, and platform constraints in business planning discussions.

• Participate in engineering delivery practices, including backlog refinement, sprint planning, design reviews, CI/CD for data pipelines,job orchestration controls, and observability for data quality and freshness.

• Contribute to initiatives spanningmetadata capture, data discoverability, governance workflows, and domainaligned ownership models, and support special projects as needed.

Qualifications

• Undergraduate degree or equivalent combination of training and experiencerequired Minimum of five years related work experience.Advanced degree in information technology or hands-on experience withdataengineering, business intelligence/analyticsengineeringpreferred.

• Two years leading large cross-functional teams on major organizational projects preferred.

Special Factors

Sponsorship

Vanguard is not offering visa sponsorship for this position.

About Vanguard

At Vanguard, we don't just have a mission—we're on a mission.

To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.

How We Work

Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.