The RoleA Portfolio Analytics Architect is responsible for leading the data validation process end-to-end with clients for data conversion projects. The ideal candidate will have a strong understanding of financial portfolio data, a motivation to work on data problems, outstanding communication skills and the ability to deliver results in adherence with project deadlines while meeting high quality standards. They are passionate about understanding our clients needs, take a hands-on approach to solving problems, work collaboratively with internal teams and take ownership of our clients success.
Addepar takes a market-based approach to pay. A successful candidate's starting pay will be determined based on the role, job-related skills, experience, qualifications, work location, and market conditions.
The range displayed on each job posting reflects the minimum and maximum target base salary for roles in Colorado, California, and New York. The current range for this role is $103,000 - $110,000 (base salary) + bonus + equity + benefits.
Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Additionally, these ranges reflect the base salary only, and do not include bonus, equity, or benefits.
Applicants must be legally authorized to work in the United States for any employer without requiring current or future visa sponsorship (for example, employment-based visas such as H-1B, F-1/OPT, or similar), and must be authorized to begin work in the U.S. on their first day of employment.
What You'll Do- Lead the data validation process end-to-end with the client and internal projects teams
- Develop scalable data analytics processes for validation in Databricks
- Write custom Python logic to detect large-scale data anomalies and automate remediation
- Facilitate recurring client sessions to track progress and steer the data validation project through to completion.
- Support clients with researching and identifying portfolio data performance discrepancies and make recommendations on how to best fix manual data issues
- Review, compare and document system calculation methodologies differences
- Coordinate across project teams communicating regular status updates for assigned data projects and while effectively setting expectations
- Mitigate project risks by effectively escalating key impediments to stakeholders and executive leadership.
- Prioritize and context-switch effectively to complete simultaneous projects; seeing each through to the finish line
- Identify and implement AI-driven automation and LLM integrations to streamline implementation
Who You Are- B.S in Finance, Mathematics, Statistics, Business or Economics
- 2+ years experience working in Technology, Finance, or Consulting
- Hands-on experience working with complex investment datasets, including multi-asset class portfolios, performance data, and market data from various sources
- Proficiency in Python, Spark, and/or SQL with familiarity of ETL fundamentals
- Working knowledge of REST APIs
- Experience with Databricks and/or a cloud-based distributed data platform
- Solution-oriented approach and a passion for problem solving
- Proven ability to research, design and implement solutions for complex problems
- Positive attitude, strong work ethic, proactive and a high contributing team player
- Independent, adaptable and can thrive in a fast-paced environment
- Excellent communication and presentation skills, with proficiency in handling client objections
