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.