Sr Data Analyst Advent Geneva

Salary is 120k to 200k + bonus

We are seeking a highly analytical Data Analyst with strong SQL expertise to support financial data analysis, reporting, and system integrations within an investment management environment. This role is heavily focused on querying large datasets, performing complex data analysis, building reports, and ensuring data integrity across multiple platforms.

• Write complex SQL queries to extract, transform, and analyze large financial datasets.
• Develop and optimize stored procedures, views, and data models to support reporting and analytics.
• Perform deep-dive data analysis to identify trends, anomalies, and reconciliation breaks.
• Partner with data engineering teams to improve database performance and data architecture.

• Analyze transactional, position, cash, and P&L data across multiple systems.
• Perform reconciliations between accounting systems, data warehouses, and downstream reporting platforms.
• Conduct root cause analysis for data discrepancies and implement long-term fixes.

• Build and maintain automated reports and dashboards using SQL and BI tools.
• Translate business requirements into technical data queries and reporting solutions.
• Support financial, operational, and regulatory reporting processes.

• Support ETL processes and data integrations between portfolio accounting platforms and other enterprise systems.
• Identify opportunities to streamline reporting workflows and automate manual processes.
• Maintain documentation for data definitions, transformations, and reporting logic.

• 4+ years of experience in a data analyst role with heavy SQL development.
• Advanced proficiency in SQL (complex joins, CTEs, window functions, performance tuning).
• Experience working with large relational databases (SQL Server, Oracle, or similar).
• Strong understanding of financial or investment data (transactions, positions, valuations, P&L).
• Experience working with Advent Geneva (required).
• Excellent analytical, troubleshooting, and problem-solving skills.

• Familiarity with ETL tools, data warehousing concepts, and data modeling.
• Experience with BI tools (Power BI, Tableau, etc.).
• Exposure to Python for data analysis or automation.