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 l