Investment Data & Analytics Engineer- Vanguard Personalized Indexing

Key Responsibilities

Investment Analytics & Tooling

• Design build and maintain Pythonbased analytics tools that support investment research portfolio analysis and operational workflows.

• Develop interactive analytics applications and dashboards using Python analytics frameworks (e.g. Plotly Dash or similar).

• Partner with investment and research stakeholders to translate analytical needs into scalable productionready solutions.

• Enable rapid experimentation while ensuring code quality reliability and maintainability.

• Investment Data Platform & Engineering

• Contribute to the design and evolution of investment data lakes and data pipelines on AWS.

• Build and maintain data ingestion transformation and access layers that support analytics and downstream investment use cases.

• Apply sound data engineering practices to ensure data quality consistency and observability.

• Collaborate with platform and architecture teams to align analytics solutions with VPIs broader data strategy.

CloudNative Development (AWS)

• Develop and operate analytics and data solutions on AWS leveraging managed services where appropriate.

• Build cloudnative scalable components that integrate with the broader VPI platform.

• Participate in CI/CD practices automated testing and operational readiness for analytics workloads.

Production Support & Team Engagement

• Participate in support and operational activities including investigation and resolution of analytics or datarelated issues.

• Contribute to oncall or support rotations as required with a focus on learning and continuous improvement.

• Actively engage in team ceremonies design discussions and code reviews.

• Continuously improve engineering practices documentation and reliability of analytics solutions.

Required Qualifications

• 3 years of professional experience in software engineering data engineering or analytics engineering.

• Strong proficiency in Python including experience with data and analytics libraries.

• Experience developing analytics or visualization solutions using frameworks such as Plotly Dash (or comparable Pythonbased tools).

• Handson experience working with AWSbased platforms.

• Familiarity with data engineering concepts such as data lakes pipelines schemas and data quality.

• Exposure to investments finance or capital markets through academic coursework or professional experience.

• Ability to operate as a handson individual contributor while collaborating effectively within a team.

Preferred Qualifications

• Experience building or working with investment or financial datasets (e.g. market data portfolios transactions).

• Familiarity with portfolio analytics investment research workflows or quantitative analysis.

• Experience with data lake architectures and analytical data stores.

• Exposure to JVMbased languages such as Java.

• Experience supporting production analytics systems in a regulated or highavailability environment.

What Success Looks Like

• You are actively building Pythonbased analytics tools that enable investment research and decisionmaking.

• You help strengthen the investment data foundation that underpins VPIs analytics and platform capabilities.

• You balance rapid analytical development with productionquality engineering practices.

• You collaborate closely with engineers investment partners and platform teams to deliver meaningful business impact.

• You grow your technical depth while contributing reliably to a missioncritical investment platform.

Special Factors

Sponsorship

About Vanguard

At Vanguard we dont just have a missionwere 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.

Future of Work

During the pandemic we transitioned to a work from home model for the majority of our crew and we continue to interview hire and on-board future crew remotely.

As we have developed the path forward we have taken a thoughtful approach that both maximizes the advantages of working remotely and the many benefits of coming together and collaborating in a shared workspace. We believe that in-person interactions among our crew are important for preserving our unique culture and advantageous for the personal development of our crew.

When our Crew return to the office many will work in our hybrid model. A smaller proportion of our crew will operate in the Work from Home work model (for example field sales crew); or in the Work from Office model (for example portfolio managers).

The working model that your role falls into will be communicated to you in the interview process please do ask if you are unsure. We encourage you to make the decision regarding your job interview and offer knowing which model your role will fall into. We will test and learn as our ways of working evolve and will continue to evaluate working models along the way.

Salary Range: