The Opportunity
The Risk & Reporting (R&R;) team is building technology-enabled performance analytics, investor reporting, and reporting-automation infrastructure across Oaktree's closed-end, open-end and evergreen strategies. The team supports roughly 1,000 recurring and custom reports and partners across investment teams, Investor Relations / Client Services, Finance / Accounting, Valuation, Data Management, Technology, Legal / Compliance, and enterprise solution groups to improve data quality, reporting speed, and production controls.
As an Associate Technical Contingent Worker resource for EM, you will lead the build, automation, refresh support, and control framework for Emerging Markets Debt dashboards, datasets, and recurring R&R; deliverables.
What You'll Do
Data Engineering & Architecture
Design and maintain cloud-ready data pipelines and dimensional models using SQL, Python, Power BI, Microsoft Fabric / Azure, and, where relevant, AWS services such as S3, Glue, Lambda, Redshift, Snowflake or Aurora;
Implement secure, automated ingestion from Oaktree systems, MDM, data warehouse sources, FTP / email feeds, vendor files, Salesforce, servicer or administrator reports, 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 to make recurring R&R; outputs auditable, repeatable, and supportable;




Use infrastructure-as-code concepts such as CloudFormation or Terraform, and orchestration patterns such as Airflow, Step Functions or Fabric pipelines where appropriate.

EM Technology & Reporting Coverage
Support Emerging Markets Debt performance, exposure, portfolio, benchmark, and investor-reporting workflows through controlled data models, dashboards, and reusable extracts;
Own technical support for EM dashboards, including Power BI / OneLake dataset refreshes, gateway issues, transformation logic, data type exceptions, and republishing coordination with Power BI Support;
Build data checks for issuer, security, region, country, currency, portfolio, valuation, cash-flow, benchmark, and performance attributes used in EM reporting;
Partner with EM investment professionals, R&R; stakeholders, Data Management, Technology, and Finance / Accounting to resolve source-data gaps and improve dashboard reliability.
Partnership & Delivery
Translate business requirements into technical specifications, delivery plans, data dictionaries, acceptance criteria, and production support playbooks;
Review analyst and associate work, mentor junior team members, and maintain clear handoffs between US stakeholders, Hyderabad delivery, Technology, and report consumers;
Use approved GenAI tools responsibly to accelerate analysis, documentation, test-case creation, and support diagnostics.
What You'll Bring
Required
5+ years in data engineering, BI development, reporting automation, or analytics engineering, preferably in asset management, investment banking, fund administration or financial services;
Strong hands-on proficiency with SQL, Python, Power BI, DAX, Power Query / M, semantic models, paginated reports,



and data validation for recurring production reporting;
Working knowledge of cloud data platforms and architecture, including Microsoft Fabric / Azure and/or AWS services such as S3, Glue, Lambda, Redshift, Snowflake or Aurora;
Familiarity with return and performance concepts such as TWR, MWR, IRR, MOIC, TVPI, DPI and RVPI, plus exposure, attribution, benchmark, and investor-reporting outputs;
Robust written and verbal communication skills, with the ability to translate investment, reporting, and data-control requirements into durable technical solutions.
Preferred
Experience with schema design, CDC, orchestration, IAM / secure data-access patterns, Git, CI/CD, CodeBuild / CodePipeline, GitHub Actions, testing, and release controls;
Familiarity with Oaktree internal reporting systems and workflows such as Geneva, IPS, Salesforce, Workday, AXON, eFront-style investor platforms, Jira, and Confluence;[NL1] [MD2]
Domain exposure to private credit, opportunistic credit, emerging markets debt, origination vehicle solutions, portfolio construction, investment performance, client reporting, or reporting operations;
AWS Data Analytics, Power BI Data Analyst, Azure / Fabric, CFA, FRM, CAIA or CIPM credentials are a plus.
How You Work
Builder's mindset, energized by replacing manual report production with controlled, well-engineered data products;
Curious, rigorous, and accountable, with the patience to investigate source-system breaks until the data, controls, and narrative hold together;
Organized and independent, able to manage technical workstreams, production incidents, documentation, reviews, and deadlines;
Team-oriented and professional, with the ability to mentor analysts and associates on durable reporting practices and technical quality standards.
Education & Credentials
Bachelor's or Master’s degree in computer science, Data Science, Engineering, Finance, Accounting or a related analytical field, or equivalent deep work experience building data / BI solutions in investment management.

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