Associate, Data Engineer

About Cresset

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.

Key Responsibilities

As part of the technology team, you will develop and maintain Cresset's data platforms in AWS, Matillion, DBT, Databricks, and Snowflake. You will work with systems of record to build and maintain data integrations, supporting our BI & AI Platforms and application integration use cases. Collaborating with senior leadership, business heads, and other data technologist, you will assess data requirements and deliver a robust data platform that drives informed, analytics-driven business decisions.

• Assist in the development of the Cresset Data Warehouse
• Assist in developing a data reporting and analytics framework, including industry best practices.
• Assist in development and maintenance of BI platforms.
• Improve the performance of queries and analysis through data modelling, tuning, and automation.
• Collaborate with business partners to prioritize and deliver against data requests and needs.
• Acquire and integrate data from multiple sources and systems for analysis.
• Present data in a clear and concise manner allowing power users to easily create their own dashboards and reports.

AI & Data Pipeline Focus

• Experience building or contributing to data pipelines that feed AI tools, including Model Context Protocol (MCP) servers or similar AI integration frameworks.
• Preparing and transforming datasets for ingestion into LLM-based tools, AI agents, or retrieval-augmented generation (RAG) systems.
• Familiarity with data formatting, chunking, schema design, or metadata tagging strategies optimized for AI tool consumption.
• Exposure to vector databases, embedding pipelines, or semantic search infrastructure.
• Understanding prompt context management and how data structure impacts AI model output quality.