Data Product Manager, Client Data

Ares Management Corporation•New York, NY

About The Position

The Data Product Manager, Client Data is a senior role within the Technology & Engineering organization, responsible for owning and driving strategy, roadmap, and delivery for core client data products. This role sits at the intersection of Data, AI, and Investor Operations, with a strong focus on client data across the investor lifecycle. The Data Product Manager will act as the primary face of the Data & AI team for assigned domains, partnering closely with Relationship Management, Investor Relations and Investor Operations stakeholders, technology teams, and external service providers to deliver scalable, high-impact data products. The ideal candidate brings deep domain experience within the asset management investor lifecycle, strong product management discipline, and a working understanding of modern data delivery platforms. This individual will be comfortable translating complex client concepts into clear data product requirements, identifying opportunities for automation and reporting, and driving continuous improvement across data operations.

Requirements

Bachelor’s Degree in Computer Science, Engineering, Information Systems, Finance, or a related field.
5+ years in data product management, analytics, or closely related roles (or equivalent experience leading data platform initiatives).
Strong knowledge of asset management investor data (e.g., fund raising pipeline, investor closings and capital activity and balances).
Hands-on experience delivering on Databricks (Lakehouse concepts, Delta Lake tables, Jobs/Workflows, notebooks, Unity Catalog governance).
Ability to define product requirements with technical depth (schemas, SLAs, lineage, quality rules) while staying outcome-focused.
Experience with modern data engineering patterns: ELT/ETL, CDC, orchestration, data modelling (dimensional and/or Data Vault), and lifecycle management.
Excellent stakeholder management and communication skills; ability to influence without authority.
Experience supporting Investor Portal initiatives with data requirements.
Experience collaborating with engineering teams on system enhancements, integrations, and data-driven solutions.
Strong understanding of data engineering concepts and investor systems integration, including ETL processes, data warehousing, and reporting platforms.
Strong client domain expertise combined with disciplined product management skills.
Excellent communication and stakeholder management abilities, with the confidence to engage senior RM, IR and Investor Operations professionals.
Ability to translate complex client concepts into clear, structured data product requirements.
Analytical mindset with a focus on data quality and delivery.
Proactive problem-solver with an eye for continuous improvement.
Comfortable operating in a fast-paced, evolving environment with multiple stakeholders and dependencies.
Expertise in Agile project management methodologies, with hands-on experience managing sprints, backlogs, and iterative delivery cycles.

Nice To Haves

Advanced degree in a Computer Science field preferred.
SQL fluency preferred; comfort reading Python code and pipeline logic (not necessarily writing production code daily).

Responsibilities

Own the data product vision and roadmap for assigned Client data domains, aligned with the Data & AI strategy and business priorities.
Partner with Investor Operations and Client Technology leadership to understand business objectives and data requirements, translating them into actionable data product initiatives.
Define clear data product goals, success metrics, and prioritization frameworks to balance near-term delivery with long-term platform evolution.
Serve as the primary data product owner for client data initiatives, ensuring clarity of scope, requirements, and outcomes.
Act as a domain expert across client data, including pre-close investor pipeline, post-close investor capital events and balances, and investor reference data.
Demonstrate strong understanding of the investor lifecycle across investor classes.
Contribute to the ongoing implementation and enhancement of the core data marketplace platform for data sourcing, processing and delivery.
Work closely with AI teams supporting the data delivery to AI use cases, including agentic workflows, LLMs and other traditional machine learning needs.
Lead discovery and requirements sessions with Relationship Managers, Investor Relations, Investor Operations and Fund Accounting to translate data needs into product capabilities (gold tables, APIs, semantic layers, feature sets).
Partner with Business Analysts, Engineers, and QA teams to translate investor data requirements into detailed user stories, acceptance criteria, and prioritized backlogs
Act as the primary liaison between RM, IR and Investor Operations team stakeholders and Data Engineering delivery teams, ensuring alignment, transparency, and timely issue resolution.
Collaborate with data engineering to design and ship pipelines using Databricks (Delta Lake, Spark, Jobs/Workflows, Unity Catalog), ensuring reliability and scalability.
Lead training and end user enablement workshops.
Identify opportunities to increase user engagement and value generated from data products.
Establish data quality standards, define SLAs/SLOs, data contracts, reconciliation controls, validation rules, and monitoring for critical datasets.
Implement domain-aligned governance (entitlements, lineage, auditability) with Unity Catalog and ensure compliance with internal and regulatory requirements.
Improve data usability: define “consumer-ready” standards, documentation, data dictionaries, sample queries, and onboarding paths.
Measure product impact: track adoption, data freshness/accuracy, time-to-insight, and business outcomes (e.g., improved reporting timeliness, reduced manual reconciliations).
Lead backlog grooming, sprint planning, and release coordination to ensure predictable, high-quality delivery.
Ensure agile practices are applied consistently, driving transparency, predictable delivery, and continuous improvement across client data initiatives.
Identify opportunities to improve investor reporting, data quality, and transparency across client data products.
Drive initiatives to automate data delivery workflows and reduce operational risk through improved data platform design and integration.
Partner with stakeholders and leadership to assess emerging capabilities, including analytics and AI-enabled solutions, where appropriate.
Serve as a visible and credible representative of Data & AI Technology initiatives to Relationship Management, Investor Relations and Investor Operations leadership.
Communicate product plans, progress, dependencies, and trade-offs clearly to both technical and non-technical audiences.
Support data governance forums, steering committees, and working sessions related to client data delivery and prioritization.

Benefits

Ares U.S. Core Benefits include Comprehensive Medical/Rx, Dental and Vision plans
401(k) program with company match
Flexible Savings Accounts (FSA)
Healthcare Savings Accounts (HSA) with company contribution
Basic and Voluntary Life Insurance
Long-Term Disability (LTD) and Short-Term Disability (STD) insurance
Employee Assistance Program (EAP), and Commuter Benefits plan for parking and transit.
access to a world-class medical advisory team
a mental health app that includes coaching, therapy and psychiatry
a mindfulness and wellbeing app
financial wellness benefit that includes access to a financial advisor
new parent leave
reproductive and adoption assistance
emergency backup care
matching gift program
education sponsorship program