Data Platform Solutions

CAIS is the pioneer in democratizing access to and education about alternative investments and structured notes for independent advisors, asset managers, and bank issuers, empowering them to engage and transact on a massive scale. We believe that the combination of industry-leading technology and human interaction throughout the pre-trade, trade, and post-trade experience delivers superior operational efficiency and a world-class client experience. CAIS provides advisors with a broad selection of alternative investment strategies, including private equity, private credit, real estate, infrastructure, hedge funds, and structured notes. CAIS serves over 2,500 wealth management firms that support more than 65,000 financial advisors who oversee approximately $8.5 trillion in end-client assets.

Role Overview 

We are looking to hire a Data Platform Solutions Lead into our Data Team. In this role, you will work at the intersection of data governance, data modeling, and internal tool development — designing and building solutions that make CAIS's data ecosystem more structured, trustworthy, and useful across the organization. AI is central to how we work and what we build — we expect this person to actively leverage AI tools in their day-to-day work and to play a key role in ensuring our data foundation is structured and governed to support CAIS's broader AI initiatives. You will collaborate closely with stakeholders across Product, Engineering, Finance, Sales, and Operations to translate business needs into scalable, AI-ready data solutions. 

Key Responsibilities 

• Design and implement scalable data models that structure raw data into clean, well-documented assets powering analytics, reporting, and downstream applications. 
• Own and drive CAIS’s data governance initiatives, including defining data ownership, establishing quality standards, and maintaining a well-cataloged and discoverable data environment. Partner with the Data Engineering team to ensure governed data assets are structured and ready for downstream integration. 
• Actively leverage AI tools across all aspects of your work — from data modeling and governance to documentation, exploratory analysis, and tool development. 
• Contribute to and guide the development of internal tools and data products that improve how teams across the firm access and act on data — including AI-assisted workflows and automation. 
• Ensure data assets are structured, governed, and well-documented to support AI and machine learning use cases, serving as a key enabler of the firm’s AI initiatives. 
• Define and enforce data quality checks, identify inconsistencies, and drive resolution across pipelines. 
• Partner with business and technical stakeholders to translate requirements into practical data solutions. 
• Document data assets, business definitions, and architectural decisions to support a shared understanding of the data ecosystem.