Oaktree Capital Management - Senior Associate/Assistant Vice President - Data Engineering & BI

Note: If screened-in, you will be invited for initial rounds on 28th November 2026 (Saturday) in Hyderabad.

Work model : Hybrid

Work from office : 3 days per week

Work from home : 2 days per week

Office shifts :

Shift 1: 1:00 PM 10:00 PM

Shift 2: 2:00 PM 11:00 PM

Responsibilities :

As a Senior Associate or AVP technical resource, you will participate in data engineering, automation, and dashboards for enterprise reporting workflows in Alternative Investment Strategies.

Data Engineering & Architecture :

- Design and maintain cloud-ready data pipelines and dimensional models using SQL, Python, Power BI, Microsoft Fabric/Azure, and AWS services (S3, Glue, Lambda, Redshift, Snowflake, Aurora).

- Implement secure, automated ingestion from Oaktree systems, MDM, data warehouse sources, FTP/email feeds, vendor files, Salesforce, and governed reporting datasets.

- Build performant ELT/ETL workflows for investment, portfolio, cash activity, audit log, exception, exposure, attribution, and reporting-control data.

- Develop reusable SQL and Python utilities, including advanced SQL optimization, window functions, pandas/PySpark data engineering, REST/GraphQL integration, validation checks, and test automation.

BI, Automation & Controls :

- Create institutional Power BI dashboards, semantic models, paginated reports, DAX measures, Power Query/M transformations, row-level security, and deployment pipeline assets.

- Troubleshoot refresh failures, gateway/OneLake dataset issues, data type conversion errors, transformation exceptions, and production publishing issues.

- Apply Git, CI/CD, release management, logging, documentation, and data-quality SLAs.

- Use infrastructure-as-code (CloudFormation/Terraform) and orchestration patterns (Airflow, Step Functions, Fabric pipelines).

Qualifications :

- 10+ years in data engineering, BI development, reporting automation, or analytics engineering in asset management, investment banking, or financial services.

- Exposure to alternative investments is required (asset-based finance, structured credit, private credit, etc.).

- Strong hands-on proficiency with SQL, Python, Power BI, DAX, Power Query/M, and semantic models.

- Working knowledge of cloud data platforms (Microsoft Fabric/Azure, AWS) and PySpark notebooks.

- Understanding of data governance, reporting standards, and compliance frameworks.

- Familiarity with return/performance concepts (TWR, MWR, IRR, MOIC, TVPI, DPI, RVPI).

Education :

- Bachelor's or Master's degree in Computer Science, Data Science, Data Analytics, Engineering, Statistics, Mathematics, Finance, Accounting, or equivalent experience.