Vanguard Australia has undergone major transformation in recent years, launching both the Direct Investment (DI) platform and our Superannuation offer. We established the Chief Data & Analytics Office (CDAO) within Technology to scale our data-driven decision making and elevate the investor and adviser experience.
CDAO’s mission is to empower Vanguard’s growth by embedding data into every decision – improving outcomes, guiding strategy, and enabling better client and crew experiences. The team spans Data Analysis, Advanced Analytics, Data Engineering, and Data Governance.

We’re seeking a Data Engineer to support the Personal Investor (PI) Data Analysis department and build high quality, scalable data solutions that power insightful decision making. This role blends hands-on engineering with functional problem solving, working closely with business leaders, CDAO teams, and broader Technology to deliver meaningful business impact.

The PI Data Analytics team partners with Marketing and Mar Tech to deliver trusted, timely data for customer insights, personalisation, and journey optimisation. Operating within the CDAO framework, the team focuses on engineering excellence, data quality, and secure enablement for analytics and activation.

In this role, you’ll design maintain reliable data pipelines and integrations that make PI data accessible for analytics and marketing activation. A key 2026 priority is enabling Adobe Experience Platform (AEP) - including capturing required data fields, establishing two way data flows with the data lake, and strengthening data quality and governance to support enhanced marketing journeys.

This hybrid role (in office Tues-Wed-Thurs) is based in Melbourne

What you will do

• Engineer scalable pipelines (e.g., Glue/Databricks, Step Functions, Lambda) to deliver timely, reliable data.

• Partner with Marketing and Martech in defining the business data needs; produce requirements, source to target mappings, and data dictionaries.

• Build two way integration between Vanguard Australia’s modern data analytics platform and Adobe Experience Platform (batch/stream), including secure ingestion and back write of activation outcomes.

• Work collaboratively within a team environment – partnering closely with PI Data Analysts to translate analytical requirements into scalable data solutions, while also working effectively with the broader data engineering community within CDAO.

• Embed data quality & governance with automated profiling, validation, reconciliation, lineage, and monitoring.

• Support & optimise existing data infrastructure with the wider Data & Analytics team to meet SLAs.

• Enable self service analytics by publishing trusted datasets and maintaining **Tableau/Power BI **dashboards.

• Document clearly (requirements, functional specs, data dictionaries, runbooks).

• Lift team capability through knowledge share sessions and collaboration in an Agile delivery model.

What you’ll bring

• Strong SQL (Py Spark & Spark SQL) and Python.

• Experience with pipeline tooling (Glue, Step Functions/Lambda).

• Proficiency in building and optimising data pipelines using Databricks across the medallion architecture

• Understanding of data modelling (dimensional/ELT/medallion), privacy/compliance, and data quality practices.

• Solid understanding of version control systems, specifically Git.

• Collaborative mindset – comfortable working with marketers, analysts, and engineers in sprints; strong written documentation.

• Proven stakeholder management and communication skills.

• Ability to document requirements, challenge assumptions, and design efficient solutions.

• Comfort working independently in complex data environments.

Nice to have

• Familiarity across the Adobe Experience Cloud stack (AEP, AJO, AEM, Target, Analytics) for data activation, personalisation, and journey optimisation.

• Basics of Tableau/Power BI and API integrations; AWS experience and IAC (Infrastructure as code).

Why This Role Is Unique

• Blend of business analysis + engineering.

• Direct impact on data strategy, solution design, and business decision-making.

• Great fit for someone who enjoys both solving technical problems and working with people.

Target start

• Early–mid March 2026, aligned to ongoing recruitment for a Data Engineer in PI Analytics.

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.