Wealth management platform with data engineering focus for family offices and institutions
Jordan Park combines traditional wealth management with a data-engineering-heavy tech stack (dbt, Snowflake, Python, Airflow, Addepar) — a pattern typical of firms moving from manual spreadsheet operations to automated, analytics-driven advisory. The project list reveals deep infrastructure work: SQL pipelines, reconciliation frameworks, and an emerging AI application layer, suggesting the firm is systematizing client portfolio and data workflows that historically required manual effort and cross-system handoffs.
Jordan Park provides investment management, wealth advice, and family office advisory to high-net-worth individuals, families, and institutional clients. Founded in 2017 and based in San Francisco, the firm operates across 51–200 employees split between finance, engineering, sales, and support. The tech infrastructure spans trading platforms (Bloomberg, FactSet), portfolio management (Addepar), data warehousing (Snowflake, dbt), and CRM (Salesforce), with active development on data pipelines, reconciliation tooling, and portfolio workflow automation.
Primary stack includes dbt, Snowflake, Python, Apache Airflow, Tableau, AWS, Docker, Kubernetes, Salesforce, and Addepar. For market data: Bloomberg and FactSet. BI tools: Power BI and Looker.
Active projects include production-grade SQL data pipelines, enterprise data platform development, AI application ecosystem build-out, reconciliation frameworks, and automation of manual operational workflows across trading and portfolio management systems.
Jordan Park Group's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.