Associate, Data Engineer

Cresset is a firm built by clients, for clients. As an independent, award-winning multi-family office and private investment firm, we are reimagining the way wealth is experienced. Our purpose is to help ensure that both wealth and life are fully optimized—integrated, intentional, and aligned with each client’s vision of success.

We provide access to the caliber of talent, ideas, and investment opportunities typically available to the largest single-family offices and institutions. Our approach is personalized, entrepreneurial, and client-first.

Proudly owned by our clients and employees, Cresset was built to endure. We are creating a 100+ year firm—one focused on delivering an exceptional experience, not only for the families we serve but for the team that serves them. Recognized by Barron’s and Forbes among the nation’s top RIA firms, and as one of the industry’s best places to work,
* Cresset is guided by long-term relationships, shared success, and a belief that wealth should serve a life well lived.

As part of the technology team, you will report to the Managing Director, Head of Investment and Data Technology, and work closely with our Senior Data Engineer focused on integrations and AI. You will help develop and maintain Cresset's data platforms in AWS, Databricks, and Snowflake, with a particular focus on building out the API and messaging layer that exposes our data to applications and AI-driven experiences.

You will work with systems of record to build and maintain data integrations into the data platforms and help design and implement the services that make that data available to consumers across the firm — including our BI platform, application integrations, and emerging AI use cases. You will collaborate with senior engineers, business partners, and department heads to assess data and integration requirements and deliver robust, well-designed data services.

The right candidate is highly proficient in Python, experienced in building and consuming APIs, and has hands-on exposure to AI tooling and the infrastructure that supports it.

Key Responsibilities

• Assist in the development of the Cresset Data Warehouse and broader data platform.
• Design, build, and maintain APIs and messaging/event-driven services that expose platform data to downstream applications, partners, and AI experiences.
• Assist in building and maintaining AI infrastructure and the integration layer connecting our data platform to AI-powered experiences (e.g., LLM integrations, retrieval pipelines, agentic workflows).
• Acquire and integrate data from multiple sources and systems — via vendor APIs, event streams, and batch processes — for analytics and application use.
• Improve the performance and reliability of data services and queries through data modeling, tuning, and automation.
• Collaborate with senior engineers and business partners to prioritize and deliver against data and integration requests.
• Contribute to API documentation, versioning, and data contracts so internal consumers can reliably build on our data services.
• Present data in a clear and concise manner, allowing power users to easily create their own dashboards and reports.

Qualifications

• Bachelor's degree in computer science, engineering, or similar.
• 2+ years of experience in data engineering, backend/integration engineering, or similar roles involving multiple IT systems.
• Strong proficiency in Python required, including experience building production-quality scripts, services, or APIs.
• Ability to code in SQL required.
• Experience working with Snowflake, Databricks, AWS, and Matillion required.
• Experience with messaging and event-driven architectures (e.g., AWS SQS/SNS, Confluent, Kafka, or similar) preferred.
• Proficiency in building and consuming API integrations (REST, webhooks), including reading vendor API documentation and staying current with tech stack updates and advancements.
• Hands-on experience working with AI technologies required — e.g., integrating LLM APIs, standing up supporting infrastructure, or building retrieval/RAG pipelines that connect data to AI experiences.
• Structured and unstructured data expertise.
• Strong analytical experience and understanding of…