Our client is looking to fill the role of Snowflake Data Engineer for a hands-on role within the Global Credit Technology team. Contribute to the ongoing development and enhancement of the Snowflake based Credit Data Warehouse, which supports portfolio analytics, loan performance monitoring, trade tracking, fund reporting, and external integrations. This role is primarily focused on data engineering, transformation frameworks, orchestration, and system integrations. This position will focus on building and maintaining reliable data pipelines, implementing business logic, and supporting scalable data solutions that power those applications. Work closely with senior stakeholders and assist the company as they modernize their technical stack.
- This fulltime position is on a hybrid schedule requiring 4 days a week on-site in Washington, DC.
- Compensation is in the $150K-$190K salary range plus bonus
- We are unable to provide sponsorship or transfer a visa for this position.
Our client is one of the worlds largest and most diversified global investment firms in Private Equity and Global Credit. The global team is comprised of more than 2,500 professionals operating in 28 offices across 4 continents.
Responsibilities:
Credit Data Warehouse Architecture & Development
- Build and enhance scalable data models within Snowflake (and Databricks where applicable) across landing, integration, and presentation layers, following established architectural patterns.
- Develop and maintain transformation logic using dbt, ensuring modular, testable, and well-documented models
- Optimize SQL performance and warehouse resource usage for large-scale financial datasets
Workflow Orchestration & Pipeline Engineering
- Build and support data pipelines orchestrated through Airflow
- Develop and maintain DAGs/workflows for ingestion, transformation, external extracts, and API integrations.
Integrations & Data Products
- Build and support integrations with external vendors, fund administrators, trustees, and internal systems.
- Build scalable export frameworks (SFTP, API, file-based extracts) driven by configuration and metadata
Applied AI & Intelligent Data Use Cases
- Support AI-enabled workflows by preparing structured and unstructured data for retrieval and analysis use cases
Required Qualifications:
Education & Certificates
- Bachelors degree required
Professional Experience
- 6 12 years of overall technical experience in data engineering
- Strong hands-on experience designing and operating solutions in Snowflake Data Warehouse
- Experience building and deploying data platforms in Azure (Azure Data Factory, Azure Storage, Azure AD)
- Strong experience writing and optimizing SQL for analytical and financial datasets
- Experience building and maintaining enterprise-grade data pipelines across ingestion, transformation, and presentation layers
- Python or other scripting experience for pipeline tooling, automation, and integration services
Preferred Qualifications:
- Experience with dbt, Airflow, APIs, or Power BI/Tableau
- Exposure to applied AI or LLM-enabled workflows in a production setting
- Exposure to financial services or alternative asset management
If you meet the required qualifications and are interested in this role, please apply today #LI-RW4