Associate, Finance Technology Data Analyst

Role & responsibilities

Business process and data understanding

• Develop a detailed understanding of how Fund Accounting data is created, enriched, transformed, reviewed, reconciled, approved, and consumed.

Requirements and business rules

- Translate Fund Accounting needs into clear business, data, integration, reporting, and broader consumption requirements for the appropriate delivery teams.

Data investigation, reconciliation, and testing

- Use SQL and structured analysis to profile data, compare sources, identify anomalies, trace records, quantify breaks, and support root-cause analysis.

• Partner with Fund Accounting, Data Governance, Data Product Management, engineering, and reporting teams to define validation rules, tolerances, exception categories, ownership, and remediation expectations.

Reporting and broader data consumption requirements

- Understand the business question, intended consumers, decisions supported, frequency, level of detail, and delivery channel for each consumption need.

• Define requirements for dashboards, reports, extracts, downstream applications, operational workflows, analytics, and other ways Fund Accounting consumes data and derives value from it.

Delivery and stakeholder partnership

- Act as the bridge between Fund Accounting business teams and Finance Technology while preserving important business and technical detail.

• Coordinate with Data Product Management, Data Governance, the Finance Technology Data Solutions Engineer, Enterprise Data Engineering, Centralized Reporting / BI, application teams, and delivery partners throughout the delivery lifecycle.

• Maintain traceability from the original business problem through requirements, design, testing, release, and validation of the delivered outcome.

Preferred candidate profile

Education: Bachelor's degree in Finance, Accounting, Information Systems, Computer Science, Engineering, Data Analytics, or a related discipline. Equivalent relevant experience will be considered.

Experience Required: 3 to 8 years in a technical data analyst, data-focused business analyst, financial data, accounting technology, or similar role in a controlled enterprise environment.

Must-have capabilities

• Strong SQL for profiling, joins, aggregations, reconciliation, anomaly detection, and root-cause analysis, preferably in SQL Server.
• Advanced Excel for structured analysis, including lookups, pivots, formulas, comparisons, and controlled validation workbooks.
• Experience defining business, data, reporting, and consumption requirements; mappings; measures; calculations; business rules; acceptance criteria; and test cases.
• Hands-on data-quality analysis, reconciliation, defect investigation, testing, business validation, and UAT.
• Ability to understand data models, ETL/ELT flows, APIs or file interfaces, reporting layers, and dependencies across source, data, and consumption layers.
• Ability to work effectively with Fund Accounting, Data Product Management, Data Governance, Finance Technology engineering, Enterprise Data Engineering, Centralized Reporting / BI, and application teams.

Strongly preferred

• Databricks, Python, PySpark, Power BI, Microsoft Fabric, Azure data services, or similar platforms.
• Fund Accounting, asset management, investor data, fund administrator, financial reporting, or investment operations experience.
• Working knowledge of accounting balances, transactions, capital activity, reference data, hierarchies, controls, and period-end processes.
• Experience defining requirements for dashboards, reports, extracts, downstream applications, operational workflows, or analytics.
• Exposure to delivery tooling, structured defect triage, release management, lineage, metadata, governance, and auditability concepts.