Lead technical resources for data engineering, automation, dashboards, and reporting workflows in alternative investment strategies.
Locations (2)
Hyderabad, Telangana, India
Los Angeles, California, United States
Responsibilities
Design and maintain cloud-ready data pipelines and dimensional models using SQL, Python, Power BI, Microsoft Fabric / Azure, and AWS services
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
Create institutional Power BI dashboards, semantic models, paginated reports, DAX measures, Power Query/M transformations, row-level security, and deployment pipeline assets
Requirements
Bachelor's or Master's degree in Computer Science, Data Science, Data Analytics, Engineering, Statistics, Mathematics, Finance, Accounting or a related analytical field, or equivalent deep work experience building data/BI solutions in investment management
Senior Data Engineer role focused on designing, developing, and optimizing data platforms, pipelines, and data products for a European business environment.
Responsibilities
Design and develop data architectures and processing workflows
Build and maintain ETL/ELT pipelines
Develop Data Lake and Big Data environments
Create new data products for analytics, reporting, and machine learning use cases
Support large-scale structured and unstructured data processing
Requirements
Informatikai, mérnöki, matematikai vagy kapcsolódó felsőfokú végzettség
Support development, integration, security, modernization, and sustainment of mission‑critical applications and data environments for the South Carolina Department of Probation, Parole, and Pardon Services.
Responsibilities
Design, develop, and maintain an enterprise data warehouse, data lake, or comparable data platform
Define data models, schemas, metadata, integration patterns, storage approaches, and lifecycle‑management practices
Establish standards for data ingestion, transformation, storage, access, retention, lineage, cataloging, quality, and security
Develop and maintain scalable ETL/ELT pipelines for batch, near‑real‑time, and real‑time data processing
Design secure, reliable interfaces among enterprise applications, reporting platforms, analytics tools, and data repositories
Requirements
Bachelor’s degree in computer science, information systems, data engineering, software engineering, or a related technical discipline
Senior Azure Data Platform Engineer / Architect to support a major enterprise data platform uplift for a leading Australian financial services organisation.
Responsibilities
Assess and uplift existing Azure data platform components.
Analyse and document dependencies across ingestion pipelines, business rules and semantic models.
Migrate and optimise ETL/ELT processes.
Develop and implement Azure data engineering solutions.
Design, build, and maintain production ETL pipelines for predictive modeling workloads.
Compensation
The pay range for the role is $82,000 to $92,000. The specific offer will depend on an applicant’s skills and other factors. This role may also be eligible to participate in a discretionary annual incentive program.
Responsibilities
Design, build, and maintain production ETL pipelines for predictive modeling workloads.
Develop and optimize PySpark jobs on Databricks, ensuring performance and reliability at scale.
Write complex, well-structured SQL for data transformation, validation, and reporting across SQL Server, Synapse Analytics, and Snowflake.
Collaborate with data scientists to understand data requirements and translate them into robust engineering solutions.
Monitor pipeline health, troubleshoot failures, and implement improvements to data quality and observability.
Requirements
Bachelor's degree in Computer Science, Information Systems, Mathematics, Engineering, or a related quantitative field.
Seeking a Tech Lead with experience in Microsoft Azure data platforms, especially Azure Synapse Analytics, to technically lead data teams, define architectures, and ensure scalable, high-quality solutions.
Responsibilities
Technically lead the data engineering/analytics team, providing technical direction, code review, and mentorship.
Design and evolve data architectures in Azure: ingestion, storage, processing, modeling, and analytical exploitation.
Implement and optimize solutions with Azure Synapse Analytics (SQL pools, Spark pools, pipelines, Data Lake integration).
Define and supervise engineering best practices: CI/CD, infrastructure as code, testing, observability, security, and data governance.
Collaborate with business, architecture, product, and technical teams to translate needs into technical solutions.
Principal Software Engineer to lead the design and implementation of the next generation PubSub solutions for customers worldwide within the Azure Event Grid engineering team.
Compensation
The typical base pay range for this role across the U.S. is USD $142,800-$274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000-$304,200 per year.
Responsibilities
Drives requirements and design by partnering with stakeholders to define and refine messaging system requirements.
Champions coding best practices, design patterns, and reusable frameworks across the team.
Defines testing strategies for messaging system components, establishing quality gates and success criteria.
Improves engineering productivity by identifying tooling gaps across the cloud messaging development lifecycle.
Drives incident response and operational excellence as a DRI.
Requirements
Bachelor's Degree in Computer Science or related technical field
Nice to have: Master's Degree in Computer Science or related technical field
Nice to have: building highly-scalable cloud services
Nice to have: building Messaging brokers or Pub Sub systems
The role focuses on building and maintaining scalable cloud-based data platforms, including product development, analytics enablement, data pipeline automation, and platform optimization using Azure data technologies for enterprise-grade solutions.
Responsibilities
Design, develop, and maintain scalable data pipelines using Azure Databricks, PySpark, and Azure Data Factory
Partner with data architects to support the full data lifecycle including acquisition, cleansing, integration, analytics, and visualization
Build and optimize Delta Tables and Azure Data Lake solutions for enterprise data platforms
Develop automated data processing services, APIs, and analytics products
Implement data governance and security controls using Unity Catalog
Requirements
BE in Computer Science
Engineering
Information Technology
Nice to have: Serverless Compute architecture on Azure
Nice to have: Data visualization and analytics product development
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