Managing Director, Head of Data Platform Engineering

Oaktree Capital Management, L.P. • Los Angeles, CA

2d

About The Position

Our Company Oaktree is a leader among global investment managers specializing in alternative investments, with more than $220 billion in assets under management. The firm emphasizes an opportunistic, value-oriented, and risk-controlled approach to investments in credit, equity, and real estate. The firm has more than 1,400 employees and offices in more than 25 cities worldwide. We are committed to cultivating an environment that is collaborative, curious, inclusive and honors diversity of thought. Providing training and career development opportunities and emphasizing strong support for our local communities through philanthropic initiatives are essential to our culture. The Data Solutions team at Oaktree Capital Management delivers trusted, high-quality data that powers the firm’s global investment and business operations. Through close collaboration with Technology and business partners, we drive data strategy, governance, and product delivery to enable reliable insights, operational efficiency, and a unified data foundation. For additional information, please visit Oaktree’s website at http://www.oaktreecapital.com/ Responsibilities As the Head of Data Platform Engineering within Oaktree’s Information Solutions organization, you will own the engineering strategy, delivery, and evolution of the firm’s enterprise data platforms. This role leads the teams responsible for building and operating both the firm’s modern cloud-based data platform and legacy data environments that support critical investment, operational, and reporting workflows. You will be responsible for delivering reliable, scalable, and well-governed data platforms that enable analytics, reporting, and data product development across the firm. The role requires strong engineering leadership, balancing platform modernization with operational stability and disciplined delivery. Working closely with Analytics Engineering, Data Operations, Data Product, Governance, and Technology teams, you will ensure that Oaktree’s data infrastructure enables trusted data, accelerates decision-making, and supports the firm’s long-term technology strategy. Responsibilities include: Data Platform Strategy & Architecture Own the engineering design, delivery, and evolution of the firm’s enterprise data platforms. Oversee the modernization and migration of legacy data environments while maintaining stability for mission-critical investment and operational workflows. Ensure platforms effectively support enterprise analytics, reporting, and data product development. Establish clear technology standards, reference architectures, and engineering guardrails to ensure consistency, scalability, maintainability, and interoperability across the data ecosystem. Partner with Architecture and Technology teams to define scalable, secure, and resilient platform standards. Engineering Delivery & Execution Own end-to-end engineering delivery across the data platform organization, from roadmap planning through implementation and transition to production. Establish engineering practices that promote reliable, scalable, and maintainable platform development. Define and track engineering delivery metrics, including velocity, reliability, cost efficiency, and platform adoption. Experience building data platforms using cloud native tech stack in Azure, AWS, Snowflake, Databricks. Building pipelines using DBT, python, and other ETL technologies. Partner with Data Products and business stakeholders to align platform capabilities with enterprise data priorities. Platform Reliability & Operational Readiness Ensure data platforms are designed and engineered for reliability, scalability, and operational supportability. Establish monitoring standards, operational guardrails, and incident response expectations for data pipelines and platform services. Partner with Data Operations team responsible for day-to-day platform monitoring and support. Participate in incident review and continuous improvement processes to strengthen platform reliability and performance. Team Leadership & Development Define the engineering operating model, standards, and development practices for the data platform organization. Lead and develop data engineering teams responsible for enterprise data platform capabilities. Oversee both modern data platform engineering teams and legacy platform teams during the transition to cloud-native architectures. Establish engineering standards and promote a culture of accountability, collaboration, and continuous improvement. Vendor & Technology Management Lead evaluation and selection of tools and vendors supporting the data platform ecosystem. Maintain a forward-looking roadmap for platform technologies, identifying opportunities to modernize capabilities in areas such as ingestion, transformation, orchestration, data quality, observability, and developer productivity. Cross-Functional Collaboration Partner with Infrastructure, Security, Architecture and other Technology teams to deliver cohesive enterprise data capabilities. Communicate platform strategy, delivery progress, and operational performance to senior leadership. Ensure platform initiatives remain aligned with enterprise data strategy and business priorities. Qualifications 15+ years of experience in data engineering, platform engineering, or enterprise data infrastructure development. Proven experience leading engineering teams responsible for building and operating enterprise data platforms. Strong experience with modern data platforms, including data warehouses, data lakes, and cloud-based data ecosystems. Demonstrated experience modernizing legacy data environments and leading large-scale platform migrations. Strong understanding of data architecture, data pipelines, orchestration frameworks, and data modeling principles. Experience implementing engineering delivery practices including CI/CD, automated testing, and operational monitoring. Experience defining and tracking engineering performance metrics such as reliability, delivery velocity, and platform adoption. Experience managing vendors, engineering consultants, and platform technology partners. Strong communication and leadership skills, with the ability to engage both technical and business stakeholders. Experience in financial services or asset management environments preferred. Deep experience leading and standardizing modern enterprise data technology stacks across cloud platforms, including data warehousing/lakehouse technologies, ELT/ETL tooling, orchestration platforms, pipeline observability, data quality, metadata, and DevOps automation. Strong technical depth across modern data ecosystem components and the ability to make informed build-versus-buy, integration, and platform standardization decisions. Personal Attributes Relationship Building; works effectively with strong, diverse teams of people with multiple perspectives, talents, and backgrounds. He or she is known for doing what is best irrespective of politics and is comfortable with consensus building (at multiple levels) and soliciting constructive feedback; ability to elicit cooperation from a wide variety of participants including upper management, clients, other departments, and 3rd party providers. Communication; strong interpersonal and verbal/written communication skills; ability to present complex material. Independence & Collaboration; experience at working both independently and in a team-oriented, collaborative environment; must be able to drive work effectively with limited supervision (at times) while representing department and executive management interests and concerns. Work Ethic; focus on continual development, performance, accountability, and self-motivation. Flexibility & Organization; adapt to shifting priorities, demands and timelines through analytical and problem-solving capabilities; proven ability to multi-task and efficiently manage time across competing activities/resources; able to effectively prioritize, execute tasks, and thrive in a high-pressure fast paced environment. Intellectual Curiosity; energized by learning new things and engaging across a wide range of issues; must have strong problem solving skills; understand the importance of attention to detail, adept at conducting research into project-related issues and products; displays a technical aptitude that lends itself to learning and mastering new technologies. Driving Results; sets aggressive timelines and objectives to drive results, conveys a sense of urgency, and drives issues to closure; is a self-starter committed to achieving results and has a strong sense of ownership and follow-through. Judgment; makes recommendations and decisions that balance a variety of factors. Education Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related discipline.

Requirements

• 15+ years of experience in data engineering, platform engineering, or enterprise data infrastructure development.
• Proven experience leading engineering teams responsible for building and operating enterprise data platforms.
• Strong experience with modern data platforms, including data warehouses, data lakes, and cloud-based data ecosystems.
• Demonstrated experience modernizing legacy data environments and leading large-scale platform migrations.
• Strong understanding of data architecture, data pipelines, orchestration frameworks, and data modeling principles.
• Experience implementing engineering delivery practices including CI/CD, automated testing, and operational monitoring.
• Experience defining and tracking engineering performance metrics such as reliability, delivery velocity, and platform adoption.
• Experience managing vendors, engineering consultants, and platform technology partners.
• Strong communication and leadership skills, with the ability to engage both technical and business stakeholders.
• Deep experience leading and standardizing modern enterprise data technology stacks across cloud platforms, including data warehousing/lakehouse technologies, ELT/ETL tooling, orchestration platforms, pipeline observability, data quality, metadata, and DevOps automation.
• Strong technical depth across modern data ecosystem components and the ability to make informed build-versus-buy, integration, and platform standardization decisions.
• Relationship Building; works effectively with strong, diverse teams of people with multiple perspectives, talents, and backgrounds. He or she is known for doing what is best irrespective of politics and is comfortable with consensus building (at multiple levels) and soliciting constructive feedback; ability to elicit cooperation from a wide variety of participants including upper management, clients, other departments, and 3rd party providers.
• Communication; strong interpersonal and verbal/written communication skills; ability to present complex material.
• Independence & Collaboration; experience at working both independently and in a team-oriented, collaborative environment; must be able to drive work effectively with limited supervision (at times) while representing department and executive management interests and concerns.
• Work Ethic; focus on continual development, performance, accountability, and self-motivation.
• Flexibility & Organization; adapt to shifting priorities, demands and timelines through analytical and problem-solving capabilities; proven ability to multi-task and efficiently manage time across competing activities/resources; able to effectively prioritize, execute tasks, and thrive in a high-pressure fast paced environment.
• Intellectual Curiosity; energized by learning new things and engaging across a wide range of issues; must have strong problem solving skills; understand the importance of attention to detail, adept at conducting research into project-related issues and products; displays a technical aptitude that lends itself to learning and mastering new technologies.
• Driving Results; sets aggressive timelines and objectives to drive results, conveys a sense of urgency, and drives issues to closure; is a self-starter committed to achieving results and has a strong sense of ownership and follow-through.
• Judgment; makes recommendations and decisions that balance a variety of factors.
• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related discipline.

Nice To Haves

• Experience in financial services or asset management environments preferred.

Responsibilities

• Data Platform Strategy & Architecture Own the engineering design, delivery, and evolution of the firm’s enterprise data platforms.
• Oversee the modernization and migration of legacy data environments while maintaining stability for mission-critical investment and operational workflows.
• Ensure platforms effectively support enterprise analytics, reporting, and data product development.
• Establish clear technology standards, reference architectures, and engineering guardrails to ensure consistency, scalability, maintainability, and interoperability across the data ecosystem.
• Partner with Architecture and Technology teams to define scalable, secure, and resilient platform standards.
• Engineering Delivery & Execution Own end-to-end engineering delivery across the data platform organization, from roadmap planning through implementation and transition to production.
• Establish engineering practices that promote reliable, scalable, and maintainable platform development.
• Define and track engineering delivery metrics, including velocity, reliability, cost efficiency, and platform adoption.
• Experience building data platforms using cloud native tech stack in Azure, AWS, Snowflake, Databricks.
• Building pipelines using DBT, python, and other ETL technologies.
• Partner with Data Products and business stakeholders to align platform capabilities with enterprise data priorities.
• Platform Reliability & Operational Readiness Ensure data platforms are designed and engineered for reliability, scalability, and operational supportability.
• Establish monitoring standards, operational guardrails, and incident response expectations for data pipelines and platform services.
• Partner with Data Operations team responsible for day-to-day platform monitoring and support.
• Participate in incident review and continuous improvement processes to strengthen platform reliability and performance.
• Team Leadership & Development Define the engineering operating model, standards, and development practices for the data platform organization.
• Lead and develop data engineering teams responsible for enterprise data platform capabilities.
• Oversee both modern data platform engineering teams and legacy platform teams during the transition to cloud-native architectures.
• Establish engineering standards and promote a culture of accountability, collaboration, and continuous improvement.
• Vendor & Technology Management Lead evaluation and selection of tools and vendors supporting the data platform ecosystem.
• Maintain a forward-looking roadmap for platform technologies, identifying opportunities to modernize capabilities in areas such as ingestion, transformation, orchestration, data quality, observability, and developer productivity.
• Cross-Functional Collaboration Partner with Infrastructure, Security, Architecture and other Technology teams to deliver cohesive enterprise data capabilities.
• Communicate platform strategy, delivery progress, and operational performance to senior leadership.
• Ensure platform initiatives remain aligned with enterprise data strategy and business priorities.

Benefits

• In addition to a competitive base salary, you will be eligible to receive discretionary bonus incentives, a comprehensive benefits package and a flexible work arrangement.

What This Job Offers

• Job Type: Full-time
• Career Level: Director
• Number of Employees: 501-1,000 employees