Alternatives Data Operations Analyst

The Role

Alts Data Operations is an Addepar team that focuses on Alternatives Investment Data.  The team collects and validates information on private funds, private companies and other non-public investments.  This data is used for our research projects on investment decision-making and deliver new research products on topics related to investing (e.g., briefs, working papers, journal articles, models). The R&I mission is to inform wealth managers and institutional investors on new ways to improve their investment performance, by helping them augment their governance, management, operations, and processes. The goal is to apply Addepar’s proprietary and private data (both quantitative and qualitative) to bring new and powerful insights to the world of investors. 

We are currently seeking an Alternatives Data Operations Analyst to work UK hours, joining our growing presence in Pune. This role will be dedicated to capturing and updating Alternatives data to power new innovations developed using a proprietary research platform. The platform aggregates over $9 Trillion in assets into an analytical data store that can be analyzed for new insights by researchers at Addepar and other prominent research institutions (e.g. London School of Economics, Dept. of Finance). The role is responsible for ensuring the platform has timely and high-quality data available. This will include oversight of the alternatives security master, data quality validations management, and workflow oversight. 

Applicants must have legal authorization to work in the country where this role is based on the first day of employment. Visa sponsorship is not available for this position.

What You’ll Do

• Work collaboratively with our UK team investigating Alternative Investment attributes during the UK working hours
• Research investments on Addepar’s global database and classify per asset type, vintage, and strategy. 
• Oversee and manage operational workflows for Alternative data processing
• Develop and maintain effective process controls and accurate metrics to ensure quality standards
• Partner with members of the Research team to implement and run data quality validations
• Oversee the security master and security classification processes 
• Own and Optimise Data Pipelines: Independently manage and troubleshoot complex end-to-end data ingestion pipelines, resolving technical blockers (e.g., networking, querying, or database errors) in partnership with engineering teams.
• Integrate AI & Developer Tooling: Proactively explore and implement AI-assisted developer tools (such as Claude Code or custom LLM prompts) to optimise repetitive workflows, streamline document parsing, and shorten validation cycles.

Who You Are

• 6+ years of financial investment/advisory industry with strong knowledge of capital markets, middle/back-office operations systems, and preferably with experience dealing with Alternatives (Private/Draw-down) Funds reporting statements and data. 
• Detailed in documenting and exhibits good follow-through techniques 
• Track record of effective problem-solving abilities, self-motivation to take on responsibility, and a strong team-player mentality
• Outstanding communication and interpersonal skills for working with clients, custodial data providers, as well as internal working partners
• Technical skills preferred in any or all of the following: Microsoft Excel, Google Suite, Atlassian Jira/Confluence, SQL, Python (Jupyter Notebook, Pandas, PySpark, etc.), Databricks, Bloomberg, Pitchbook, or other common financial services systems and applications
• Hands-on SQL & Data Warehouse Experience: Strong proficiency using SQL and Databricks (PySpark) to navigate complex data architectures, extract custom audits, and validate high-volume datasets.
• Familiarity with Modern AI Developer Tools: Exposure to or a strong interest in using AI tools (e.g., Claude Code, GitHub Copilot, or automated API integrations) to optimize code and speed up daily data operational workflows.
• Alternative Asset Document Literacy: Exceptional ability to interpret unstructured private market financial data (such as Form D filings, capital account statements, or institutional investment briefs) and translate them into clean, structured database taxonomies.