Data Platform Solutions Lead
Cais · New York, New York
About this role
## Data Platform Solutions Lead ### About CAIS CAIS is a 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 at massive scale. We combine industry-leading technology with human interaction across the pre-trade, trade, and post-trade experience to deliver superior operational efficiency and a world-class client experience. CAIS provides advisors with alternative investment strategies including private equity, private credit, real estate, infrastructure, hedge funds, and structured notes. CAIS serves over 2,500 wealth management firms supporting more than 65,000 financial advisors overseeing approximately $8.5 trillion in end-client assets. ### Role Overview We’re looking to hire a **Data Platform Solutions Lead** into our Data Team. In this role, you’ll 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. You’ll actively leverage AI tools day-to-day and help ensure our data foundation is structured and governed to support CAIS’s broader AI initiatives. You’ll 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—partnering with the Data Engineering team to ensure governed data assets are structured and ready for downstream integration. - **Actively leverage AI tools** across data modeling and governance, documentation, exploratory analysis, and tool development. - **Contribute to and guide internal tools and data products** that improve how teams 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. - **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. ### Skills & Experience Required - Demonstrated experience applying **AI tools in a data context** (data governance, data modeling, or pipeline development), with a track record of leveraging AI to drive efficiency and better outcomes. - Experience in **data engineering, analytics engineering, or data architecture** (ideally within financial services or fintech). - Strong proficiency in **SQL** and experience with **Snowflake** for data warehousing and transformation. - Hands-on experience with **dbt** for data modeling and workflow management. - Working knowledge of **data governance concepts** and tooling; experience with platforms like **DataHub, Collibra, or Alation** is a plus. - Demonstrated
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