Data Platform Solutions Lead at CAIS

New York, New YorkFull-timeTechnologyPosted about 2 months ago

About the Role

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  <ul> <li>Design and implement scalable data models that structure raw data into clean, well-documented assets powering analytics, reporting, and downstream applications. </li> <li>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. </li> <li>Actively leverage AI tools across all aspects of your work — from data modeling and governance to documentation, exploratory analysis, and tool development. </li> <li>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. </li> <li>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. </li> <li>Define and enforce data quality checks, identify inconsistencies, and drive resolution across pipelines. </li> <li>Partner with business and technical stakeholders to translate requirements into practical data solutions. </li> <li>Document data assets, business definitions, and architectural decisions to support a shared understanding of the data ecosystem. </li> </ul> Skills & Experience Required  <ul> <li>Demonstrated experience applying AI tools in a data context — including data governance, data modeling, or pipeline development with a track record of leveraging AI to drive efficiency and better outcomes. </li> <li>Experience in data engineering, analytics engineering, or a data architecture role, ideally within financial services or fintech. </li> <li>Strong proficiency in SQL and experience with Snowflake for data warehousing and transformation. </li> <li>Hands-on experience with dbt for data modeling and workflow management. </li> <li>Working knowledge of data governance concepts and tooling; experience with platforms like DataHub, Collibra or Alation is a plus. </li> <li>Demonstrated ability to build internal tools or data products that solve practical business problems. </li> <li>Strong communication skills with the ability to engage both technical and non-technical stakeholders. </li> </ul> Highly Advantageous Skills  <ul> <li>Familiarity with Python for data processing or automation. </li> <li>Experience with BI and data visualization tools such as Tableau. </li> </ul> CAIS is consistently recognized as a Best Place to Work, and our culture is at the heart of our success. We are committed to fostering an inclusive environment where employees can be their most authentic selves and feel inspired and supported to bring their voice forward to drive community, growth, and innovation. We are an equal opportunity employer, and do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law.  Learn more about our culture, benefits, and people at <a href="https://www.caisgroup.com/our-company/careers">https://www.caisgroup.com/our-company/careers</a>.    CAIS’ compensation package includes a market competitive salary, a performance bonus, and exceptional benefits. If you are located in New York, New York, the base salary range for this role is $170,000 – $200,000. Actual compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, and specific office location.  CAIS offers a comprehensive benefits package that includes generously subsidized healthcare with 100% employer paid dental and vision insurance, an employer matched retirement plan, wellness programs, and generous PTO and parental leave. Additionally, CAIS offers a flexible, hybrid in-office model; for most roles, we do require a minimum of 3 days in either our New York City or Austin office per week.  For more information on our benefits and career opportunities, please visit our website: <a href="https://www.caisgroup.com/our-company/careers">https://www.caisgroup.com/our-company/careers</a>.   We use technology, including AI tools, to support parts of our recruitment process such as application screening, interview scheduling, and candidate communications. These tools are used to improve efficiency and consistency, but they do not replace human judgement. All hiring decisions are made by people, and we are committed to fair and unbiased assessment of every candidate.

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