Lead Portfolio Analytics Architect

Accountabilities

• 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.

• 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.

• Recruitment and Resource Planning: Assess staffing requirements and collaborate with recruitment teams to attract, interview, select, and onboard qualified professionals.

• 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.

• 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.

• 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.

• 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.

• 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.

Requirements

• Education: Bachelor's degree in Finance, Mathematics, Statistics, Engineering, Business, Economics, or a related discipline. Progress toward CFA or FRM certification is an advantage.

• 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.

• 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.

• Technical Skills: Proficiency in Python, Spark, and/or SQL, with a solid understanding of ETL fundamentals and working knowledge of REST APIs.

• Data Platforms: Experience with Databricks or other cloud-based distributed data platforms, ideally involving large-scale data processing and analytics.

• Leadership and Management: Proven ability to lead, coach, motivate, and develop teams while establishing clear objectives, managing performance, and driving accountability.

• Analytical and Problem-Solving Skills: Strong ability to investigate complex challenges, identify root causes, design practical solutions, and implement process improvements.

• Project Management: Excellent organizational and prioritization skills, with the ability to manage competing deadlines, coordinate multiple initiatives, and consistently deliver results.

• Communication and Collaboration: Strong written and verbal communication skills, including the ability to document technical findings, present team achievements, and collaborate effectively with international stakeholders.

• Personal Attributes: Proactive, adaptable, independent, and solution-oriented, with a strong work ethic, positive attitude, and collaborative mindset.

• Global Collaboration: Flexibility to work hours that regularly overlap with teams based in the United States and the United Kingdom.

• Additional Advantages: Previous experience with investment management software implementations or Salesforce is a plus.

Benefits

The original job posting does not specify a detailed benefits or compensation package. However, the opportunity offers:

• A leadership position with the opportunity to shape and grow an expanding Data Analytics practice.

• The opportunity to work on complex financial data challenges and large-scale technology initiatives.

• Exposure to innovative technologies, including AI-driven automation, LLM integrations, Python, Spark, and Databricks.

• Opportunities for professional development, technical growth, and leadership advancement.

• Collaboration with international teams and exposure to global investment management projects.

• An inclusive and collaborative working environment that values ownership, innovation, continuous learning, and teamwork.

• Equal employment opportunities and reasonable accommodations throughout the recruitment and employment process.

Important employment information:

• Location: Pune, India.

• Visa sponsorship is not available. Candidates must be legally authorized to work in India from their first day of employment.

• Working hours: Flexibility is required to regularly overlap with US and UK teams. The application also specifies a UK shift of 2:30 PM–11:30 PM IST.

• Relocation to Pune may be required for candidates currently based elsewhere.