Lead Portfolio Analytics Architect
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Key details
- Location
- India
- Work style
- Remote
- Level
- Lead / Staff+
- Job type
- Full-time
- Experience
- 5–8 yrs
- Function
- Software engineering
- Focus area
- Data engineering & Analytics
- Posted
- 3h ago
Skills
About the role
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Lead Portfolio Analytics Architect based in India.
As a Lead Portfolio Analytics Architect, you will lead a team of data professionals responsible for ensuring the accuracy, integrity, and quality of complex financial portfolio data. You will combine people leadership with hands-on technical expertise to oversee end-to-end data validation projects and drive operational excellence. Working with investment datasets, analytics platforms, and cloud-based technologies, you will develop scalable solutions that improve efficiency and automate workflows. You will also play a key role in shaping the team's strategy, strengthening internal processes, and introducing AI-driven innovations. Collaborating with global stakeholders across multiple regions, you will ensure consistent project delivery and high-quality client outcomes. This is an opportunity to influence a growing analytics practice while developing talent and solving challenging data problems.
Accountabilities
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Team Leadership and Development: Lead, mentor, and manage a team of Portfolio Analytics Architects, balancing managerial responsibilities with hands-on project delivery. Establish clear objectives, performance metrics, and priorities while ensuring consistent productivity and high-quality outcomes.
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Performance Management: Conduct regular one-to-one meetings, performance reviews, and career development discussions. Support employee onboarding, identify development opportunities, delegate responsibilities, and foster a culture of accountability and continuous improvement.
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Recruitment and Resource Planning: Assess staffing requirements and collaborate with recruitment teams to attract, interview, select, and onboard qualified professionals.
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Data Analytics and Validation: Oversee end-to-end data validation projects involving complex investment portfolios, ensuring accuracy, consistency, and reliable results. Develop scalable data analytics processes using Databricks and create custom Python solutions to detect large-scale data anomalies and automate remediation.
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Process Optimization and Automation: Identify opportunities to streamline workflows, improve internal tools, and increase operational efficiency. Introduce AI-driven automation and Large Language Model (LLM) integrations to support scalable implementation processes.
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Strategic Leadership: Drive internal management initiatives and contribute to the development and execution of the Data Analytics practice strategy. Collaborate with regional leaders to improve team performance, operational consistency, and service delivery.
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Project and Stakeholder Management: Coordinate multiple projects simultaneously, manage priorities, monitor execution, and ensure deadlines are met. Communicate complex findings and project updates clearly while escalating risks and resolving delivery challenges.
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Best Practices and Quality Assurance: Establish and promote consistent methodologies, technical standards, and best practices to ensure reliable, high-quality data solutions across projects and teams.
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Education: Bachelor's degree in Finance, Mathematics, Statistics, Engineering, Business, Economics, or a related discipline. Progress toward CFA or FRM certification is an advantage.
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Professional Experience: At least 5 years of experience in technology, finance, consulting, fund accounting, or investment operations, with demonstrated experience managing teams, projects, and cross-functional initiatives.
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Financial Data Expertise: Hands-on experience working with complex investment datasets, including multi-asset-class portfolios, investment performance data, and market data from multiple sources.
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Technical Skills: Proficiency in Python, Spark, and/or SQL, with a solid understanding of ETL fundamentals and working knowledge of REST APIs.
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