Senior Data Analytics Engineer

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Ultimus Fund Solutions

WebsiteLinkedInAll Job Openings

501 - 1000 employees

💸 Finance

☁️ SaaS

🤝 B2B

💰 Private equity on 2012-07

Finance • SaaS • B2B

Ultimus Fund Solutions is an independent provider of fund administration and investment operations solutions for advisors and asset/fund managers. The firm delivers high-touch, scalable services across public and private markets — including transfer agency, middle-office and investment operations, ETF launch and conversion support, and specialized administration for mutual funds, private equity, private credit, retail alternatives, REITs and other fund wrappers. Ultimus combines these services with integrated, AI-enabled technology platforms (Ultimus Connect, Portfolio Analytics Portal, Workflow Manager, Investor and Advisor Portal, Private Investor Portal and related tools) to provide data, reporting and workflow automation. According to its public materials it administers $775B+ in assets, supports 2,500+ funds, 450+ clients, and 1,200+ associates.

📋 Description

• Develop and maintain analytical models, dashboards, and data products • Partner closely with application development, data engineering, and business teams • Deliver scalable, well-governed analytics solutions • Design and develop Power BI reports, dashboards, and semantic data models • Build and maintain statistical models and forecasting tools • Ensure data accuracy and integrity across reporting outputs • Stay current with emerging trends in data science, analytics engineering, and business intelligence tooling.

🎯 Requirements

• 3+ years of experience in data science, analytics engineering, or business intelligence • Strong hands-on development and deployment of Power BI reports and data models in production environments. • Experience querying and working with data in Snowflake or similar cloud data platforms. • Financial services experience, ideally supporting fund administration or asset management platforms. • ETL/ELT tools and modern data engineering frameworks. • Regulatory and compliance considerations related to financial data. • Statistical analysis, data wrangling, and exploratory data analysis techniques. • Machine learning or predictive modeling techniques applied to business use cases. • Proficiency in Microsoft Office Suite and Adobe Acrobat.

🏖️ Benefits

• Health insurance • Professional development opportunities