Lead Portfolio Analytics Architect
Addepar (company site, opens in a new tab)5+ yrsPuneOn-siteDirect career pageEst. 25–40 LPA
Posted 2h ago
Reach people at Addepar
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Addepar you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Lead and manage a team of Portfolio Analytics Architects responsible for end-to-end data validation in data conversion projects, ensuring high-quality deliverables.
- Drive continuous improvement by identifying opportunities to scale, automate workflows, and enhance internal tooling and processes.
- Develop and mentor team members including performance management, staffing, and career development while collaborating across regions to optimize efficiency and deliver consistent results.
Minimum Requirements
- 5+ years of experience in Technology, Finance, Consulting, fund accounting, or investment operations.
- Bachelor’s degree in Finance, Mathematics, Statistics, Engineering, Business, Economics, or a related field.
- Proficiency in Python, Spark, and/or SQL; experience with Databricks or cloud-based distributed data platforms.
- Legal authorization to work in the country of employment on the first day; visa sponsorship not available.
Ideal Candidate Profile
- Experienced leader with proven ability managing teams and cross-functional projects, capable of balancing hands-on technical skills with managerial responsibilities.
- Strong background working with complex multi-asset class investment datasets, including performance and market data from various sources.
- Skilled in designing and implementing scalable, automated data analytics and validation solutions utilizing modern tools such as Python, Spark, Databricks, and AI-driven automation.