Vice President, Data Ingestion & Integration

 Ares Management is seeking a Vice President, Data Ingestion & Integration to help design, build, and scale the firm's enterprise data ecosystem. This role will be responsible for delivering highly scalable data engineering solutions that enable analytics, reporting, operational efficiency, and AI-driven capabilities across Ares' global business.

The successful candidate will possess deep technical expertise, demonstrate ownership of critical platform components, and work closely with business stakeholders, architects, and engineering teams to advance the firm's data strategy.

Supervises: n/a

·       Define and own the enterprise Data Ingestion & Integration strategy and multi-year roadmap.

·       Establish standards, governance, and best practices for enterprise-wide data movement and integration.

·       Build and lead high-performing engineering teams responsible for ingestion, integration, and data connectivity services.

·       Drive adoption of modern, event-driven, API-first, and cloud-native integration patterns.

·       Partner with product teams to prioritize strategic data initiatives aligned to business growth objectives.

·       Develop operational KPIs and SLAs for data delivery, platform reliability, scalability, and quality.

·       Drive modernization initiatives, including migration from legacy data warehouses and on-premises platforms to Azure.

·       Build cloud native data ingestion frameworks supporting:

o   Structured and unstructured data

o   Internal operational systems

o   Third-party data providers

o   Market data feeds

o   Alternative data sources

o   Partner ecosystems

·       Design scalable data onboarding processes reducing time-to-market for new data sources.

·       Lead implementation of reusable ingestion accelerators, metadata-driven pipelines, and self-service onboarding capabilities.

·       Establish standards for batch, micro-batch, and streaming ingestion architectures.

·       Ensure observability, lineage, monitoring, reconciliation, and operational supportability across ingestion solutions.

·       Establish enterprise-wide observability standards for all ingestion and integration services.

·       Implement comprehensive monitoring, alerting, telemetry, and operational dashboards across the data ecosystem.

·       Develop proactive incident detection and automated remediation capabilities.

·       Establish centralized visibility into pipeline health, data freshness, throughput, latency, and service availability.

·       Partner directly with stakeholders across Investment Operations, Finance, Compliance, Investor Relations, Risk, and Investment teams.

·       Translate complex business requirements into scalable technical solutions.

·       Drive successful delivery of strategic data initiatives and enhancements.

·       Implement and support data quality controls, lineage, metadata, and governance capabilities.

·       Contribute to data security, privacy, and compliance requirements.

·       Establish technical standards and engineering best practices.

·       Lead technical workstreams and complex engineering initiatives.

·       Mentor junior team members and provide technical guidance.

·       Participate in architecture discussions and technology evaluations.

·       Collaborate with leadership on platform roadmap and prioritization efforts.

• 12+ years of experience in enterprise data engineering, integration, or platform engineering.
• 8+ years of leadership experience managing large technical organizations.
• Proven experience building enterprise-scale data ingestion and integration platforms.
• Extensive experience leading cloud transformation initiatives.
• Demonstrated success building and retaining high-performing engineering teams.
• Experience operating in highly regulated industries such as financial services, banking, insurance, healthcare, or asset management preferred.

·       Extensive experience (12+ years) designing and implementing enterprise-scale data ingestion platforms utilizing Azure Data Factory, Azure Databricks, Delta Lake, Unity Catalog, and Azure Data Lake Storage for batch, near real-time, and streaming data workloads.

·       Deep expertise in building metadata-driven, reusable, and scalable ingestion frameworks supporting onboarding of internal systems, SaaS applications, third-party providers, market data feeds, and external data providers, while enforcing enterprise standards for governance, security, and operational controls.

·       Strong hands-on experience with Databricks, Apache Spark, Python, SQL, Delta Lake, Delta Live Tables (DLT), and Databricks Workflows to develop high-performance data integration and transformation solutions with built-in data quality and pipeline reliability controls.

·       Proven experience implementing event-driven and real-time integration architectures leveraging Apache Kafka, Confluent Platform, Azure Event Hubs, Azure Service Bus, Change Data Capture (CDC), and Databricks Structured Streaming to enable scalable and resilient enterprise data movement.

·       Strong experience implementing enterprise observability, telemetry, monitoring, alerting, and audit capabilities utilizing Azure Monitor, Log Analytics, Application Insights, Azure Data Factory Monitoring, Databricks Lakehouse Monitoring, Databricks System Tables, Databricks Job Monitoring, Azure Workbooks, and Microsoft Sentinel, providing proactive visibility into pipeline health, data freshness, throughput, latency, SLA adherence, and operational performance.

·       Deep expertise establishing end-to-end lineage, reconciliation, and audit frameworks utilizing Unity Catalog Lineage, Delta Lake transaction logs, data quality scorecards, reconciliation controls, exception management, and automated operational dashboards, ensuring full traceability, compliance, and trusted data delivery across the enterprise.