Risk, Reporting & Analytics-Tech

Oaktree Capital Management; Hyderabad; Hybrid; INR 2,600,000 - 3,800,000; Full time

Job summary

Oaktree Capital Management in Hyderabad invites an AVP/Senior Associate to lead data engineering, automation, and enterprise reporting workflows for Alternative Investment Strategies. You will design cloud-ready pipelines, implement secure ingestion, build ELT/ETL processes, and develop reusable Python utilities while collaborating with US stakeholders and Hyderabad delivery.

Strong SQL, PySpark, Power BI and cloud experience are essential, with a proven track record in data governance,

Qualifications

• 10+ years in data engineering, BI development, or analytics engineering.
• Experience in asset management or financial services preferred.
• Strong SQL, Python, and Power BI proficiency.
• Cloud platforms (Azure and AWS) required.
• Experience with Fabric pipelines and PySpark a plus.

Responsibilities

• Design and maintain cloud-ready data pipelines and dimensional models.
• Build ELT/ETL workflows for investment and reporting data.
• Create Power BI dashboards and semantic models.
• Ensure data quality, governance, and auditable outputs.
• Collaborate with multidisciplinary teams and stakeholders.

Skills

SQL

Python

Power BI

Azure

AWS

Data modeling

Pandas/PySpark

Git/CI-CD

Data governance

Stakeholder communication

Tools

Microsoft Fabric

Azure

AWS S3

AWS Glue

AWS Lambda

Redshift

Snowflake

Aurora

Databricks

Synapse

Job description

Role & responsibilities

As an Assistant Vice President/Senior Associate technical resource for our team, you will participate in data engineering, automation, dashboards for enterprise reporting workflows in Alternative Investment Strategies. Responsibilities include:

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.

Technology & Reporting Coverage

• Support Private Markets reporting workflows through controlled data models, dashboards, reusable extracts, and exception monitoring;
• Build and maintain Power BI / Salesforce-enabled pipeline and enterprise dashboard logic, including deal-stage filters, region filters, expected close dates, accruing-expense flags, and unique deal identifiers;
• Develop checks and exception logs for deal IDs, expense tracking, vendor-fee workflows, Workday tagging, budget fields, Salesforce data quality, and downstream hand-offs to Investment Operations, Fund Accounting, Tax, Investment Team, Investor Relations, Client Services and other enterprise solution users;
• Partner with investment teams, Technology, Finance / Accounting, Tax, administrators, and enterprise solution groups to improve pipeline data quality and reduce ad hoc information requests.

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.

Preferred candidate profile

• 10+ years in data engineering, BI development, reporting automation, or analytics engineering, preferably in asset management, investment banking, fund administration, financial services or another data-rich domain with comparable rigor;
• Exposure to alternative investments is required, with domain experience in asset-based finance, structured credit, private credit, opportunistic credit, emerging markets debt or origination vehicle solutions strongly preferred;
• 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;
• Hands-on experience developing Microsoft Fabric pipelines, dataflows, Lakehouse and data warehouse solutions, together with PySpark notebooks for distributed data processing in Fabric, Databricks or Synapse Spark environments;
• Working knowledge of the broader Azure data stack, including Azure Data Factory, Azure Synapse Analytics, Azure Data Lake Storage, Azure DevOps, and SQL Server Management Studio for querying, data modeling and performance optimization;
• Experience designing scalable, reusable Power BI solutions using common data models, common measures, standardized layouts and consistent navigation, with semantic-model security including row level and object-level security;
• Understanding of data governance, reporting standards and compliance frameworks, with a nonnegotiable focus on data integrity, accuracy, clear naming and documentation;
• Familiarity with return and performance concepts such as TWR, MWR, IRR, MOIC, TVPI, DPI and RVPI, plus exposure, attribution, benchmark, and investor-reporting outputs;
• Strong written, verbal and presentation skills, with the ability to translate investment, reporting and data-control requirements into durable technical solutions and explain technical design choices and trade-offs to senior stakeholders and deal-team partners.