Assistant Vice President - Senior Data Engineer

Oaktree is a leader among global investment managers specializing in alternative investments, with $224 billion in assets under management.  The firm emphasizes an opportunistic, value-oriented and risk-controlled approach to investments in credit, private equity, real assets and listed equities.  The firm has over 1500 employees and offices in 26 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. For additional information please visit our website at www.oaktreecapital.com .

As an AVP within Oaktree's Information Solutions team, you will be responsible for the integration of data operations within our data engineering frameworks, ensuring that our technical implementations are aligned with long-term scalability and sustainability. This role is pivotal in bridging the gap between engineering and business operations, enabling seamless transitions from development to deployment and maintaining the quality and integrity of our data assets. You will be tasked with building robust operational processes that support the firm’s data-driven decision-making while ensuring that data operations are fully integrated into our technical environment for future growth.

Summary As an AVP, you will be joining our Data Solutions group. This is a senior individual contributor role that will play a critical part in designing and building the next‑generation technology platform supporting Oaktree’s credit business—one of the firm’s largest and most sophisticated investment strategies.  Hands-on data engineering role: Work directly in building ETL/ELT data pipelines, validating data patterns, exception handling, maintaining data quality, ensuring data security standards and deploying production-grade systems daily; ideal for data engineers who prefer building over managing. High ownership & autonomy: Collaborate with global stakeholders (primarily Los Angeles-based) while independently driving problem identification, solution design, execution, and communication. data-intensive development: Build data pipelines that support batch/real time data processing, develop central data platform seamlessly with all self-service capabilities such as data integrations/orchestrations, governance and analytics. Product-focused data engineering: Build data products such as Index Hub, MDM, Performance Dashboard, Job Monitoring Dashboard includes health check of system performance etc. and own delivery end-to-end to support data management life cycle Modern cloud data architecture: Contribute to an evolving Azure-based platform, influencing scalable, reliable system design with practical, experience-driven decisions. Applied generative AI: Leverage AI tools to improve engineering efficiency and enhance product capabilities in a practical, results-driven way. Responsibilities include: Develop and implement data workflows (fast ingestion, transformation, analytics, APIs), semantic models, data operations dashboards are designed for long-term scalability and efficiency. Collaborate closely with data engineering teams to define and implement operational processes that align with data pipeline architectures, ensuring robust and scalable data solutions. Define and develop a robust data quality rule(s) across data domains and critical data assets that proactively monitors and resolves quality issues, partnering with data owners and data stewards throughout the organization. Look for performance optimizing techniques, diagnosing data issues, performing root cause analysis, and working directly with technical teams or business stakeholders to remediate issues and develop corrective actions. Manage the day-to-day activities of data operations, ensuring that data