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 operating 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