Data Projects Analyst

The Role

Part of the broader Addepar Data organisation, the Data Client Projects team is responsible for converting and onboarding existing client portfolio data onto Addepar. During the lifecycle of a project, members of this team will coordinate data transmission/extraction, transform and import data, and assist with the validation of the data. Accurate and timely completion of these projects are crucial in enabling our clients to take full advantage of Addepar's reporting and analysis capabilities.

Applicants must have, and maintain, the right to work in the United Kingdom from the first day of employment. Please note that visa sponsorship is not available for this role.

What You’ll Do

• Manage and complete data conversion projects of varying complexity from third-party systems and files sourced from our custodial data partners.
• Partner with members of Sales and Services organisations to drive alignment on project cost estimates and deliverables, and to ensure positive client outcomes.
• Develop new/improve existing python scripts and Juptyer notebooks to interact with APIs.
• Collaborate with Product and Engineering to identify and implement process improvements and tooling enhancements that increase operational efficiency.
• Maintain team resources and procedural documentation, and ensure metrics are accurately recorded for internal analytics.

Who You Are

• 3+ years of work experience in the financial investment/advisory/technology industry with strong understanding of capital markets and portfolio accounting.
• Proven track record of multitasking and prioritising effectively in a fast paced environment, and experienced in leading cross-functional projects.
• Outstanding communication and interpersonal skills for engaging with clients, data providers, as well as internal partners.
• Demonstrates effective problem solving abilities, self-motivation to take on responsibility, and a strong team-player mentality.
• Willing to work flexible hours.
• Technical skills preferred in any or all of the following: Microsoft Excel, Google Suite, Atlassian Jira/Confluence, SQL, Salesforce, Python (Jupyter Notebook, Pandas, Requests, etc.), Bloomberg, Thomson Reuters, or other common financial services systems and applications.