Portfolio Data Analyst

Arcana Analytics; Coimbatore District; On-site; INR 600,000 - 1,000,000; Full time

Job summary

Arcana Analytics seeks a dynamic Portfolio Data Analyst to support onboarding and success teams, translating financial data into actionable strategies for clients.

You'll collaborate with founders, financial analysts, product managers, and engineers to integrate data from diverse sources, improve pipelines, and deliver reliable data solutions across Arcana's platform.

Qualifications

• Experience analysing financial data and investment management concepts.
• Strong written and verbal communication for vendors, clients, and internal teams.
• Ability to articulate complex problems and solutions clearly.
• Experience collaborating with engineering, product, and data teams.

Responsibilities

• Analyze and onboard portfolio data from multiple sources into Arcana's data ecosystem.
• Collaborate with engineering, product management, and data operations to deliver reliable data solutions.
• Work with third-party data providers to integrate their data into Arcana's system.
• Develop data aggregation solutions based on client and third-party content.
• Collaborate with UX, design, and project management to develop data-oriented workflows and product improvements.
• Analyze and implement solutions to improve data operations and pipeline efficiency.
• Understand Arcana's products and clients, identify opportunities to serve them and grow the business.
• Contribute to the evolution of Arcana's financial data solutions for market-traded and alternative asset data.

Skills

Data analysis

Finance exposure

Stakeholder communication

Documentation writing

Data modeling

Cross-functional collaboration

Job description

We are seeking dynamic Portfolio Data Analysts to join our team and collaborate closely with our founders, financial analysts, product managers, and engineers. In this role, you'll play a pivotal part in supporting our client onboarding and success team. You'll need a strong ability to analyze financial data, translate insights into actionable strategies, and effectively guide clients through our platform's features to drive their success.

Responsibilities:

• Analyze and onboard portfolio data from various sources into Arcana's data integration ecosystem.
• Collaborate with engineering, product management, and data operations teams to deliver high-quality, timely, and reliable data solutions through Arcana's platform.
• Work with a range of third-party data providers to integrate their data into Arcana's system.
• Develop and support data aggregation solutions based on client and third-party content, tailored to user workflow needs.
• Collaborate with user experience, design, and project management teams to develop data-oriented workflow solutions and product enhancements.
• Analyze and implement solutions to improve data operations and pipeline efficiency.
• Understand Arcana's products and clients, working closely with internal stakeholders to identify new opportunities to serve clients and grow the business.
• Contribute to the evolution of Arcana's financial data solutions, ensuring the platform remains a leading integrator of market-traded and alternative asset data.

Requirements:

• GPA of 8.0+
• Data analysis experience with exposure to finance and investment management.
• Strong communication and interpersonal skills for collaborating with vendors, clients, and internal teams.
• Ability to communicate complex ideas, problems, and solutions clearly both verbally and in writing for development, sales, clients, and third-party data providers.
• Ability to work with engineering teams to define functional and technical solutions to business problems, including a solid understanding of data development, data modeling, and writing/reviewing technical documentation.
• A passion for the finance and technology space, with a focus on solving complex problems in the investment management industry.
• Experience working with financial data and concepts relevant to Arcana's clients and products is highly preferred.