The Data Analyst will manage and analyze large financial datasets, design data quality frameworks, perform data validation, and deliver insights through dashboards and reports while collaborating with various stakeholders.
Arcana is a portfolio intelligence platform used by hedge funds and asset managers to analyze performance and risk. We’re rethinking the tools institutional investors rely on—and we’re hiring analysts who want to help drive that transformation.
We are looking for a Data Analyst to work with large-scale financial datasets, ensure high data quality, and deliver actionable insights through dashboards and reports.
The role focuses on building and maintaining robust data quality frameworks and collaborating closely with internal and external stakeholders at scale.
Responsibilities
- Manage and analyze large volumes of daily financial data
- Design, implement, and continuously improve data quality frameworks
- Perform data validation, reconciliation, and monitoring
- Resolve Level 1 & Level 2 data quality issues; escalate complex issues to Data Science teams
- Use SQL and Python for data analysis, scripting, and development
- Build and maintain dashboards and reports for business insights
- Work with large-scale datasets (100TB+) covering 100K+ global companies
- Apply statistical techniques to monitor data accuracy and anomalies
- Collaborate with cross-functional teams and share insights with stakeholders
Requirements
- Strong understanding of data quality, validation, and reconciliation concepts
- Advanced SQL skills (complex queries, joins, performance optimization)
- Proficiency in Python for data analysis and scripting
- Experience with dashboarding and reporting tools
- Ability to work in large-scale / big data environments
- Working knowledge of statistics for data monitoring and validation
- Strong communication and stakeholder management skills
- Experience handling data from multiple and diverse sources
Qualifications
- Bachelor’s degree in BCA / MCA / Engineering
- CGPA: 8+
- Prior experience in Finance / FinTech preferred
- Exposure to financial datasets is a plus
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