Data Associate

• Data Associate
• Company: Arcana
• Job Location: India
• Employment Type: Full-time

We are seeking a detail-oriented Data Associate to join our growing team. As a Data Associate, you will work closely with our product managers, financial analysts, and engineers to ensure high-quality data integration, analysis, and maintenance. The ideal candidate will have a passion for working with large datasets, a strong analytical mindset, and a desire to make an impact in the financial technology space.

• Responsibilities:
• Work with large datasets to ensure data accuracy, consistency, and integrity across databases.
• Partner with Product and Engineering teams to identify and implement process improvements and automation tools to enhance data quality and operational efficiency.
• Support internal teams by creating and maintaining internal reports and dashboards.
• Diagnose and highlight data pipeline issues, escalating complex problems as needed.
• Respond promptly to data-related inquiries and requests from clients, internal teams (Sales, Services), and external data providers/partners.
• Collaborate with regional teams on shared operational workflows and cross-functional projects.
• Maintain and update team resources and procedural documentation, and ensure accurate recording of metrics for internal reporting and analytics.
• Conduct daily verification checks to ensure the accuracy and timely availability of client portfolio data, adhering to defined SLAs.
• Requirements:

Bachelor's degree in a relevant field (Mathematics, Statistics, Data Science, Finance, Economics, or related disciplines).GPA of 8.0+ is requiredStrong understanding of data management and analytics.

• Proficiency in Excel and/or other data analysis tools.
• Excellent communication and interpersonal skills for engaging with internal and external data partners.
• Consistent track record of multitasking and prioritizing effectively in a fast-paced environment, and remaining calm under pressure.
• Open to working flexible hours (early morning, day shift, evening shift) .