AVP, Client Platforms - Data Architect

• Lead the Client Platform Data Engineering function, responsible for ingestion, transformation, modeling, orchestration, storage and delivery of Ares’ Client data
• Have primary accountability for aligning to Ares’ data governance standards including modeling, lineage, data quality, and data protection standards
• Own the design and operation of enterprise data lakes and Lakehouse architectures, supporting client use cases.
• Apply best-in-class engineering standards for data pipelines, CI/CD, testing, and data quality assurance

• Partner with the Data and AI organization to define and apply data reference architectures
• Partner with Infrastructure, Platform Engineering, Security, and Architecture teams to ensure scalability, resiliency, data privacy and regulatory compliance.
• Promote modern engineering practices including DevOps, Automated testing and data quality assurance
• Ensure platforms meet enterprise requirements for security, auditability, privacy, and regulatory controls.

• Own end-to-end engineering delivery, from roadmap execution through production operations.
• Establish delivery metrics (velocity, reliability, cost efficiency, platform adoption).
• Lead vendor selection and management for data related tooling.
• Ensure platform stability, uptime, and support for mission-critical investment and client workflows.

• Build and lead a high-performing engineering team.
• Develop leaders and succession pipelines.
• Foster a strong engineering culture focused on quality, accountability, innovation, and continuous improvement.

• 12+ years of progressive technology experience, with significant leadership experience in data  architecture, design and delivery
• Proven experience building and operating enterprise-scale data platforms, ideally in asset management, alternatives, banking, or similarly complex regulated environments.
• Demonstrated success leading teams
• Strong track record partnering with senior business and technology leaders

• Deep hands-on understanding of:
• Cloud platforms (Azure preferred; AWS/GCP experience welcome)
• Databricks, Lakehouse architecture, and modern data stacks
• Salesforce data modeling
• Data Modelling, including lineage and transformation
• Data quality assurance
• Experience integrating commercial AI tools with proprietary data preferred

• Bachelor’s degree required, advanced degree preferred.
• Engineering or Computer Science background strongly preferred.

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.