Investment Data & Analytics Engineer- Vanguard Personalized Indexing

Key Responsibilities

Investment Analytics & Tooling

• Design, build, and maintain Python‑based 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, production‑ready 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 VPI’s broader data strategy.

Cloud‑Native Development (AWS)

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

• Build cloud‑native, 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 data‑related issues.

• Contribute to on‑call 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 Python‑based tools).

• Hands‑on experience working with AWS‑based 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 hands‑on 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 JVM‑based languages such as Java.

• Experience supporting production analytics systems in a regulated or high‑availability environment.

What Success Looks Like

• You are actively building Python‑based analytics tools that enable investment research and decision‑making.

• You help strengthen the investment data foundation that underpins VPI’s analytics and platform capabilities.

• You balance rapid analytical development with production‑quality 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 mission‑critical investment platform.

Special Factors

Sponsorship

Vanguard is 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.

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