Investment Data & Analytics Engineer- Personalized Indexing

Key Responsibilities

• 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.

• Contribute to 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.

• 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.

• 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.

• 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.

• 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.

• 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.

Vanguard is offering visa sponsorship for this position.

$90,000.00 - $