Senior Vice President, Senior Data Engineer

Our Company

Oaktree is a leader among global investment managers specializing in alternative investments, with $205 billion in assets under management as of December 31, 2024. 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 1200 employees and offices in 23 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

Responsibilities

As a Senior Data Engineer within Oaktree's Information Solutions team, you will design, build, and maintain scalable and efficient data pipelines using Azure technologies, ensuring data quality, integrity, and availability for various business needs. You will play a crucial role in integrating data from diverse sources, transforming it into meaningful insights, and enabling data-driven decision-making across the organization.

Responsibilities include:

• Designing and implementing scalable and secure data processing pipelines using Azure Data Factory, Azure Databricks, and other Azure services.
• Develop code using ETL and ELT processes to transform data from Bronze to Silver, and Gold layer of maturity of data
• Ensure DevOps for code development and deployment.
• Perform Unit testing, system testing, QA testing and integrated engineering. Automated testing.
• Managing and optimizing data storage using Azure Data Lake Storage, Azure SQL Data Warehouse, and Azure Synopse, Microsoft Fabric.
• Developing data models and maintaining data architecture to support data analytics and business intelligence reporting.
• Ensuring data quality and consistency through data cleaning, transformation, and integration processes.
• Analyses current business practices, processes, and procedures as well as identifying future business opportunities for leveraging Microsoft Azure Data & Analytics Services.

Technical Responsibilities:

• Develop and maintain robust data pipelines using Azure Data Factory, orchestrating the flow of data from various sources, including Bloomberg, FactSet, Morningstar, and internal systems.
• Utilize Azure Databricks (or similar Azure tech stack) to perform data transformations, cleansing, and aggregations, preparing data for analysis and reporting purposes.
• Implement data quality checks and validation rules to ensure the accuracy, completeness, and consistency of data throughout the data lifecycle.
• Develop and maintain data models for investment data, ensuring alignment with business requirements and supporting efficient data analysis and reporting.
• Optimize data storage and retrieval processes using Azure Data Lake Storage, Azure SQL Database, and Azure Cosmos DB, Azure Synopse, or Azure Fabric selecting the most appropriate storage solutions based on data characteristics and performance needs.
• Collaborate with data scientists and business analysts to understand data requirements and implement data solutions that meet those needs effectively.
• Contribute to the development and maintenance of documentation related to data pipelines, data models, and data quality processes.

Qualifications

• Bachelor’s degree in Computer Science, Finance, or other relevant discipline.
• 10+ years of experience in data and analytics space and 8+ years of experience in job specific work.
• Knowledge of the asset management industry and asset classes to bridge business and technology for data solutions.
• Strong understanding of key data concepts (e.g., Portfolio Construction, Security/Account Reference data, AUM, Investment Results/Attribution, Index/Benchmark).
• Experience with industry data (e.g., Bloomberg, FactSet, Morningstar, ESG, Index, alternative data).
• Hands-on experience with data warehouse, data lake, and cloud solutions, collaborating with data engineering teams.

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 l