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Salary: USD 86,000 - 134,000 / annual
Addepar is a global data and AI platform that empowers investment professionals to transform complex financial information into actionable intelligence. The company unifies portfolio, market, and client data to deliver AI-powered insights within investment and client workflows. With over 1,400 firms managing nearly $9 trillion in assets across nearly 60 countries, Addepar operates a sophisticated platform integrating with 650+ software, data, and consulting partners.
The Portfolio Data Operations Analyst role sits at the nexus of Addepar's operations, ensuring clients receive timely, high-quality data. The Data Operations team manages transaction and position processing to meet client timelines, implements verification checks to maintain data quality, and provides data support to clients. This position requires daily collaboration with data providers, clients, and cross-functional teams across the organization.
Key responsibilities include performing daily internal verification checks on portfolio account data to ensure accuracy and SLA compliance; investigating and troubleshooting data pipeline issues and feed processing exceptions, escalating to Engineering Support when needed; maintaining and optimizing operational workflows; collaborating with Client Support, Solution Architects, Services, and Sales teams to resolve client data inquiries; partnering with Product and Engineering to design and test new processes and tooling that improve data quality and operational efficiency; and participating in company-wide initiatives to launch new product functionality.
The ideal candidate brings 2+ years of experience in the financial investment or advisory industry with deep knowledge of capital markets, trade processing and lifecycle, and middle/back-office operations systems. Strong attention to detail, problem-solving passion, excellent communication skills, and proven ability to multitask in a fast-paced environment are essential. Technical proficiency in Microsoft Excel, VBA, SQL, Python, Salesforce, Bloomberg, Thomson Reuters, or similar financial services systems is preferred. The role requires a team-oriented, determined, and forward-thinking mindset.
