Data Analyst - Finance Technology

Over the last 20 years, Ares’ success has been driven by our people and our culture. Today, our team is guided by our core values – Collaborative, Responsible, Entrepreneurial, Self-Aware, Trustworthy – and our purpose to be a catalyst for shared prosperity and a better future. Through our recruitment, career development and employee-focused programming, we are committed to fostering a welcoming and inclusive work environment where high-performance talent of diverse backgrounds, experiences, and perspectives can build careers within this exciting and growing industry.

Job Description

PRIMARY FUNCTIONS & RESPONSIBILITIES

Business process and data understanding

• Develop a detailed understanding of how Fund Accounting data is created, enriched, transformed, reviewed, reconciled, approved, and consumed.
• Work with Fund Accounting, Data Governance, and Data Product Management to define business problems, intended outcomes, priorities, users, business rules, data ownership, and acceptance criteria.
• Identify sources of truth, data owners, business definitions, transformation points, downstream consumers, dependencies, controls, and process handoffs.
• Analyze current-state processes and data flows to identify manual work, duplicate logic, data issues, control gaps, and standardization opportunities.

Requirements and business rules

• Translate Fund Accounting needs into clear business, data, integration, reporting, and broader consumption requirements for the appropriate delivery teams.
• Define field definitions, measures, calculations, dimensions, filters, hierarchies, business rules, mappings, acceptance criteria, and expected outcomes.
• Partner with Data Governance and Data Product Management on data ownership, definitions, quality expectations, lineage, control requirements, prioritization, and decision records.
• Develop source-to-target mappings, data dictionaries, process flows, requirements, and traceability artifacts in collaboration with the teams responsible for implementation.
• Frame requirements clearly enough for the Finance Technology Data Solutions Engineer, Enterprise Data Engineering, Centralized Reporting / BI, and application teams to design, build, test, and deliver solutions that meet business objectives.

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.
• Perform field-level and aggregate analysis to distinguish source, transformation, reference-data, integration, and reporting issues.
• Partner with Fund Accounting, Data Governance, Data Product Management, engineering, and reporting teams to define validation rules, tolerances, exception categories, ownership, and remediation expectations.
• Develop and execute reconciliation, integration, regression, edge-case, reporting, and production-validation test scenarios as part of the broader delivery team.
• Create repeatable queries and validation packs that can be reused by the broader team.

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.
• Identify governed sources of truth and document measures, calculations, dimensions, filters, business rules, refresh expectations, control expectations, reconciliation needs, and validation criteria.
• Convey agreed business requirements to Centralized Reporting / BI, which owns the technical build and delivery of scalable dashboards and reporting solutions using governed data.
• Coordinate Fund Accounting review, business validation, UAT, release readiness, and post-production validation for reporting and other consumption solutions.

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.
• Communicate issues clearly, including affected users and data, business impact, evidence, decisions needed, and recommended next steps.
• Help convert recurring manual investigation into prioritized backlog items and governed, reusable, scalable data or consumption solutions.

QUALIFICATIONS

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 with Investran OR Geneva.
• 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.

How success will be measured

• Business, data, reporting, and consumption requirements are clear, complete, testable, and aligned to business objectives.
• Data issues are identified and resolved faster through repeatable analysis, clear evidence, and coordinated ownership.
• Reconciliation, testing, business validation, and UAT produce reliable delivery outcomes.
• Fund Accounting consumption needs are translated into governed, scalable solutions delivered through the appropriate Finance Technology, enterprise data, reporting, or application team.
• Strong collaboration, traceability, and handoffs are established across the broader data and reporting operating model.

Reporting Relationships

There is no set deadline to apply for this job opportunity. Applications will be accepted on an ongoing basis until the search is no longer active.