Associate - Data Quality & Monitoring

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 a Data Quality & Operations Associate within Oaktree's Data Solutions team, you will be responsible for building data quality rules across various data domains and critical data sets/attributes and maintain integrity, freshness, completeness and trustworthy of data for the downstream consumers without any business impact. This role is pivotal in bridging the gap between data engineering and business operations, maintaining high quality and integrity of our data assets across the source/target systems. You will be tasked with building robust data quality/operational model/processes that support the firm’s data-driven decision-making while ensuring that data quality operations are fully integrated into our technical environment for future growth. Responsibilities include: Populate data quality rules/validations across critical data at an enterprise into data quality template by effectively co ordinating with business/technical teams for long-term scalability and efficiency. Develop and implement a cohesive data quality and exception handling practice that proactively monitors and resolves quality issues, partnering with data data owners, data stewards throughout the organization. Serve as the primary line of defense for diagnosing data quality 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 quality monitoring/operations, ensuring data pipelines are efficiently and accurately catching data quality issues and exception handling, with minimal/zero disruption to downstream users. Collaborate with technology and data governance teams to ensure upstream data issues are addressed and that validation processes are updated as necessary to ensure long-term data integrity, freshness and completeness. Develop performance metrics and KPIs to measure the effectiveness of data quality in the form of DQ Dashboard, continuous improvement without compromising in the quality.

6+ years of experience in data management, data operations, data quality, cataloging and monitoring. Knowledge of the asset management industry and financial data concepts.  Experience in a fast-paced, exacting data environment. Familiar with semantic data models, modern data architecture such as Kimbal, medallion, fabric etc. Expertise in building data quality rules/ validation frameworks, and data governance processes, with the ability to integrate operational practices into engineering frameworks for long-term scalability. Familiarity with querying tools (e.g., SQL), Python, Monitoring the job schedules, system performance health checks on daily basis, sending alerts to downstream teams for any data load delays or breaching the SLAs, diagnosing issues from job status/logs and generating data quality dashboards in Power BI or any other visualization tools. Triaging the issues by effectively coordinating with business/data engineering development teams for permanent fixes and communicate Root Cause Analysis (RCA) across all the users . Expertise in Data Quality, Data Catalog/Lineage tools such as Microsoft Purview, Alation a plus