Data Product Manager, Operations Data

Ares Operations•Los Angeles, CA

About The Position

The Data Product Manager, Operations Data is a senior role within the Technology & Engineering organization, responsible for owning and driving strategy, roadmap, and delivery for core operational and reference data products. This role sits at the intersection of Data, AI, and Operations, with a strong focus on investment operations data across the investment lifecycle. The Data Product Manager will act as the primary face of the Data & AI team for assigned domains, partnering closely with Investment 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 investment lifecycle, strong product management discipline, and a working understanding of modern data delivery platforms. This individual will be comfortable translating complex investment operations 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 operations data (e.g., reference data, performance, treasury and investment-related operational data).
Experience with real estate operational data, including asset data, real estate investment structures and tenant management data.
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 collaborating with engineering teams on system enhancements, integrations, and data-driven solutions.
Strong understanding of data engineering concepts and investment operations and MDM systems integration, including ETL processes, data warehousing, and reporting platforms.
Strong operations domain expertise combined with disciplined product management skills.
Excellent communication and stakeholder management abilities, with the confidence to engage senior Operations professionals.
Ability to translate complex operations 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

Product Strategy & Roadmap Ownership
Own the data product vision and roadmap for assigned Operations data domains, aligned with the Data & AI strategy and business priorities.
Partner with Investment Operations and 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 operations data initiatives, ensuring clarity of scope, requirements, and outcomes.
Operations Data Domain Leadership
Act as a domain expert across operations data, including investment reference data, performance, treasury and fund and investment accounting.
Demonstrate strong understanding of the operations lifecycle across investment classes, including private credit, private equity and real estate.
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.
Delivery Execution & Cross-Functional Collaboration
Lead discovery and requirements sessions with Investment Operations to translate data needs into product capabilities (gold tables, APIs, semantic layers, feature sets).
Partner with Business Analysts, Engineers, and QA teams to translate operations data requirements into detailed user stories, acceptance criteria, and prioritized backlogs
Act as the primary liaison between 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 and 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 operations data initiatives.
Data, Reporting & Automation Enablement
Identify opportunities to improve reporting, data quality, and transparency across operations 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.
Stakeholder Engagement & Communication
Serve as a visible and credible representative of Data & AI Technology initiatives to Operations and Technology 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 operations 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.
Ares offers a number of additional benefits including 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, and much more.

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