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 :

The Senior Data Engineer will join the Data Solutions team and focus on building, enhancing, modernizing, and supporting central distributed cloud data platforms within the investment management, portfolio and asset management domains. The role requires strong hands-on engineering experience across backend/API development, data pipelines, SQL/data warehousing, CI/CD, and Azure cloud services.

The ideal candidate should have prior asset management or investment management experience, including hands-on exposure to performance contribution/attribution, benchmark/index data and MDM - Security Master, Account Master etc.

The person should be a self-starter who can work right from understanding Jira requirements, understanding ETL/ELT architectures, data pipeline design, test and deliver high-quality data pipeline deployments/implementations across dev/uat/prod environments by closely with US/Global data engineering teams and other business stakeholders.

Position Summary :

- 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, Central MDM across master data domains such as Security Master, Account Master etc.., Performance Contribution/Attribution, Performance Dashboards, Central Job Monitoring includes health check of system performance etc., Incident Management and Data Quality Metrics and own delivery end-to-end to support data management life cycle.

- Modern cloud data architecture: Contribute to an evolving Microsoft Fabric, Azure-based platform, influencing scalable, reliable system design with practical, experience-driven decisions.

- Applied generative AI: Leverage AI tools such as Claude Codex, ChatGPT to improve engineering efficiency and enhance product capabilities in a practical, results-driven way.

Responsibilities include :

- Develop, enhance, modernize, and support applications, APIs, data pipelines, and reporting components for performance attribution reporting and index/master data platforms in Fabric/Azure.

- Work from documented Jira requirements, clarify business or technical questions where needed, estimate work, and translate requirements into reliable technical implementation.

- Build backend services, APIs, and web application components using C#/.NET and Python.

- Develop and support data pipelines using Azure Data Factory and internal or custom ETL/ELT tools.

- Write complex SQL queries, stored procedures, and data processing logic in MS SQL Server; optimize query and batch performance.

- Support data warehouse solutions, including dimensional models, fact and dimension structures, reporting data marts, and historical data handling.

- Own production support for attribution reporting and index/master data platforms, including troubleshooting, data issue resolution, stability improvements, release support, and occasional after-hours/on-call support for critical issues.

- Perform unit testing, integration testing, regression testing, data validation, reconciliation checks, and support UAT with business users.

- Interact with business teams such as performance, attribution, portfolio analytics, operations, and investment reporting teams to clarify requirements, validate outputs, and resolve issues.

- Support CI/CD, release management, environment coordination, and deployment activities using Azure DevOps and Git.

- Refactor existing applications, APIs, data pipelines, and reporting components to improve maintainability, performance, scalability, and reliability.

- Prepare and maintain technical documentation, implementation notes, runbooks, production support procedures, release notes, and knowledge transfer materials.

- Follow secure coding practices, data governance standards, auditability requirements, and control processes appropriate for investment reporting and data platforms.

- Provide informal technical guidance to other developers through code reviews, implementation guidance, best practices, and knowledge sharing.

Qualifications :

- 8+ years of professional software engineering experience.

- Strong hands-on experience with Python development.

- Experience with backend/API/web application development.

- Strong experience with MS SQL Server, including complex SQL, stored procedures, query optimization, and performance tuning.

- Experience with Azure Data Factory, DBT and ETL/ELT data pipeline development, including internal or custom ETL platforms.

- Experience with Git, branching strategies, code reviews, and collaborative development practices.

- Experience with Azure DevOps, CI/CD pipelines, build/deployment automation, release management, and environment coordination.

- Experience with Azure cloud services such as Azure Functions, App Services, Storage Account, Entra ID, Azure Event Bride, Logic Apps, Service Bus, or similar capabilities.

- Strong understanding of data warehouse concepts, including dimensional modeling, fact and dimension tables, historical data, reporting marts, and data quality controls.

- Experience working in Agile/Scrum delivery models, including Jira or Azure Boards, user stories, estimation, sprint planning, and delivery ceremonies.

- Strong troubleshooting, analytical, and problem-solving skills.

- Strong written and verbal communication skills, with the ability to work effectively with US-based technology teams, business stakeholders, architects, managers, and support teams.

- Experience building or integrating AI-assisted developer productivity tools, LLM-based code-generation assistants, automated code review tools, test-generation utilities, or workflow automation using platforms such as GitHub Copilot, OpenAI Codex, ChatGPT, or similar tools.

- Practical experience applying AI-assisted development practices to improve engineering productivity, code quality, documentation, testing, and release workflows.

- Experience with Power BI for reporting, validation, analytics support, or business-facing data review.

- Experience with front-end frameworks such as .NET, ReactJS.

- Experience modernizing legacy applications, data pipelines, and reporting processes.

- Experience supporting high-availability or business-critical reporting platforms.