Senior Data Solutions Engineer - 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 ==================================== **Finance Technology Data Solutions** * Design, build, test, deploy, and support Finance Technology data solutions that serve Fund Accounting processes and operating requirements. * Define and implement Fund Accounting-specific transformations, reconciliation and control logic, data-quality rules, integrations, and data products. * Develop integrations with fund administrators, Fund Accounting systems, files, APIs, and other domain sources in partnership with the teams that own the relevant platforms. * Develop Finance Technology data products and integrations required to support Fund Accounting processes, controls, reporting, analytics, and operational workflows. * Use SQL Server, Databricks, Python, PySpark, APIs, and related technologies to deliver scalable solutions from design through production support. **Data quality, reconciliation, and controls** * Build validation, reconciliation, exception-management, monitoring, and control capabilities as part of shared delivery with Fund Accounting, Data Governance, Data Product Management, and engineering partners. * Build and support validation, reconciliation, monitoring, exception-management, and control capabilities aligned with agreed business, data-quality, and control requirements. * Support investigation and resolution of data issues through technical evidence, root-cause analysis, and sustainable remediation. * Maintain appropriate lineage, documentation, test evidence, observability, and operational support procedures for Finance Technology-owned solutions. **Enterprise platform alignment and partnership** * Leverage enterprise platforms, pipelines, governed data layers, shared engineering capabilities and patterns, and reusable enterprise data products. * Partner with Enterprise Data Engineering on Fund Accounting requirements, source data, enterprise integrations, domain transformations, data-quality expectations, controls, and consumption needs. * Contribute Fund Accounting domain expertise to enterprise data products and initiatives so enterprise data can be reliably applied to Fund Accounting use cases. * Align Finance Technology solutions with enterprise-wide engineering standards while maintaining ownership of domain-specific solutions and delivery outcomes. **Data Products & Downstream Consumption** * Build Finance Technology data products that support Fund Accounting operational processes, dashboards, reports, analytics, extracts, downstream applications, and other consumption needs. * Design scalable data models, transformations, controls, reconciliations, and interfaces that enable consistent downstream consumption. * Deliver governed datasets, technical definitions, lineage, refresh processes, and quality controls required for reporting and other downstream use cases. * Partner with Centralized Reporting / BI by providing trusted data products and technical foundations required for scalable reporting solutions. * Support the ongoing operation, monitoring, enhancement, and lifecycle management of Finance Technology data products. **Business partnership and engineering discipline** * Collaborate across Finance Technology, Fund Accounting, Enterprise Data Engineering, Data Governance, Data Product Management, Centralized Reporting / BI, application teams, and delivery partners throughout the delivery lifecycle. * Apply sound practices for data modeling, performance, security, access control, retention, testing, deployment, and environment management. * Use Git, peer review, automated testing, CI/CD, controlled releases, and documented rollback and support procedures. * Communicate technical issues in clear business language and make practical trade-offs while maintaining accountability for Finance Technology outcomes. QUALIFICATIONS ============== **Education:** Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, or a related discipline. Equivalent relevant experience will be considered. **Experience Required: 5 to 8 years of hands-on data engineering, data solutions, or financial technology experience, ideally within financial services, asset management, accounting, investment operations, or another controlled enterprise data environment.** **Must-have capabilities** * Advanced SQL Server skills, including complex queries, stored procedures, performance tuning, and troubleshooting. * Hands-on Databricks experience, including notebooks, workflows/jobs, Spark concepts, Delta Lake patterns, and production support. * Python and/or PySpark for transformation, validation, automation, and testing. * Strong ETL/ELT, data modeling, integration, and curated-data-layer experience. * Experience building domain-specific transformations, integrations, data products, validation, reconciliation, monitoring, and controls. * Ability to own technical delivery while working effectively within a broader enterprise data and reporting operating model. * Git, pull requests, automated testing, deployment pipelines, and disciplined software delivery. **Strongly preferred** * Azure Data Factory, Data Lake Storage, Azure DevOps, Microsoft Fabric, APIs, JSON, and secure file-transfer patterns. * Experience with Fund Accounting systems, fund administrator data, financial balances, transactions, capital activity, or multi-system reconciliations. * Working knowledge of metadata, lineage, catalog, master/reference data, governance, controls, and auditability concepts. * Experience structuring governed data for dashboards, reports, extracts, downstream applications, operational workflows, and analytics. **How success will be measured** * Fund Accounting data is reliably transformed, reconciled, controlled, and applied to operational and consumption use cases. * Finance Technology data products are trusted and usable across dashboards, reports, extracts, downstream applications, workflows, and analytics. * Enterprise capabilities are reused where appropriate without weakening Finance Technology ownership of domain-specific solutions and outcomes. * Domain-specific integrations, transformations, reconciliations, and controls reduce manual work and recurring data issues. * Clear accountability and strong handoffs are established across the broader data and reporting operating model. **Reporting Relationships** Principal, Business Operations Systems _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._