Data Engineer, Global Credit Technology

1P284 THE CARLYLE GROUP EMPLOYEE CO., LLC; Washington (District of Columbia); On-site; USD 150,000 - 170,000; Full time

Job summary

The Carlyle Group is seeking a Data Engineer, Credit Data & Applications to help build and maintain the Credit Data Warehouse (CDW) powering portfolio analytics, loan monitoring, and reporting. You will implement data pipelines, transformation logic with dbt, and reliable integrations across Snowflake/Databricks environments.

The role emphasizes pipeline orchestration with Airflow, data quality and governance, and collaboration with investment and operations teams to deliver scalable data

Qualifications

• Bachelor's degree in a quantitative field required; concentration in CS/engineering preferred.
• Minimum 6 years of relevant data/engineering experience.
• Strong hands‑on experience with Snowflake and/or Databricks; SQL optimization for large financial datasets.
• Experience building data pipelines with dbt and orchestration with Airflow; API/file‑based integrations desirable.
• Familiarity with Azure and/or AWS cloud environments and BI tooling (Power BI).

Responsibilities

• Build and enhance scalable data models in Snowflake/Databricks across landing, integration and presentation layers.
• Develop and maintain transformation logic with dbt; ensure modular, tested models.
• Design and optimize SQL for performance and cost in large datasets.
• Implement data quality checks, lineage, governance and audit controls.
• Collaborate with analytics teams to support reporting and BI needs (Power BI).

Skills

SQL

Python

Power BI

Airflow

dbt

Data modeling

Communication

Education

Bachelor's degree

Master's degree

Tools

Snowflake

Databricks

dbt

Airflow

Azure

AWS

Power BI

Job description

Position Summary

The Data Engineer, Credit Data & Applications is a hands‑on engineering role within Carlyle's Global Credit Technology team. This individual will contribute to the ongoing development and enhancement of the Credit Data Warehouse (CDW), which supports portfolio analytics, loan performance monitoring, trade tracking, fund reporting, and external integrations. The role is primarily focused on data engineering, transformation frameworks, orchestration, and system integrations. While the team builds applications on top of CDW, dedicated application engineering resources lead full‑stack UI development.

The position will focus on building and maintaining reliable data pipelines, implementing business logic, and supporting scalable data solutions that power those applications. The ideal candidate has strong hands‑on experience with modern cloud data platforms (Snowflake and/or Databricks), transformation tooling (dbt), and orchestration frameworks (Airflow or similar). This individual works effectively in a business‑aligned environment, partnering with investment and operations teams to deliver secure and scalable data solutions.

Primary Responsibilities

Credit Data Warehouse Architecture & Development (40%)

• Build and enhance scalable data models within Snowflake (and/or 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.
• Implement data quality checks, validation rules, and audit controls.
• Contribute to metadata‑driven approaches that support flexible integrations and reporting needs.
• Support lineage, governance, and maintainability of CDW assets through documentation and adherence to engineering standards.
• Design data models optimized for reporting and BI consumption, partnering closely with the Credit IQ (Power BI) team to ensure scalable semantic layers and performant analytics.

Workflow Orchestration & Pipeline Engineering (25%)

• Build and support data pipelines orchestrated through Airflow.
• Develop and maintain DAGs/workflows for ingestion, transformation, external extracts, and API integrations.
• Support improvements to pipeline reliability, monitoring, and error handling in production environments.
• Collaborate with DevOps to ensure CI/CD alignment and production stability.
• Support modernization of legacy orchestration processes into Airflow‑based frameworks.

Integrations & Data Products (20%)

• 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.
• Support data consumption by internal applications and analytics tools.
• Collaborate with application engineering teams to provide well‑structured datasets and data interfaces for application use.

Applied AI & Intelligent Data Use Cases (10%)

• Support AI‑enabled workflows by preparing structured and unstructured data for retrieval and analysis use cases.
• Assist in enabling retrieval‑based workflows leveraging CDW datasets where applicable.
• Ensure AI‑related datasets follow security and governance standards.

Cross‑Functional Collaboration & Technical Leadership (5%)

• Participate in code reviews and provide guidance to junior and offshore contributors.
• Coordinate assigned work with offshore resources to ensure clarity of requirements and timely delivery.
• Work with investment and operations teams to translate business workflows into scalable data solutions.
• Promote clear documentation and adherence to engineering best practices.

Requirements

Education & Certificates

• Bachelor's degree, required.
• Concentration in computer science, engineering, or a related quantitative field, preferred.
• Master's degree, preferred.

Professional Experience

• Minimum of 6 years of overall relevant technical experience, required.
• Experience in data engineering, platform engineering, or backend‑focused software engineering roles, required.
• Strong hands‑on experience designing and operating solutions in Snowflake and/or Databricks (or comparable modern cloud data warehouse/lakehouse platforms).
• Experience building and deploying data platforms in Azure and/or AWS cloud environments.
• Strong experience writing and optimizing SQL for analytical and financial datasets.
• Hands‑on experience with dbt for transformation management, testing, and modular model development.
• Experience developing and supporting Airflow‑based orchestration pipelines (or equivalent), including workflow design and monitoring.
• Experience building and maintaining enterprise‑grade data pipelines across ingestion, transformation, and presentation layers.
• Experience integrating enterprise systems via APIs, file‑based transfers (SFTP), or event‑driven workflows.
• Exposure to financial services, alternative asset management, or credit products strongly preferred.
• Experience collaborating with offshore or distributed engineering teams preferred.
• Experience supporting reporting and BI environments (e.g., Power BI), including building reporting‑friendly data models and optimizing warehouse performance for analytics workloads.
• Python experience for pipeline tooling, automation, and integration services.
• Experience with Azure services (e.g., Azure Data Factory, Azure Storage, Azure AD) and/or AWS services (e.g., S3, IAM, Lambda, ECS).
• Experience building or supporting data services consumed by applications.
• Exposure to applied AI or LLM‑enabled workflows in a production setting.
• Familiarity with Power BI or comparable BI/reporting tools and semantic modeling concepts.
• Strong SQL and analytical data modeling skills.
• Snowflake and/or Databricks fundamentals, including performance and cost considerations.
• dbt framework design and transformation best practices.
• Airflow (or equivalent) orchestration and production support experience.
• Azure and/or AWS cloud‑native data architecture.
• API integration and service‑oriented data patterns.
• Data quality, lineage, governance, and audit controls.

Competencies & Attributes

• Strong problem‑solving and analytical skills.
• Ability to translate business workflows into scalable data solutions.
• Clear communication with both technical and non‑technical stakeholders.
• Understanding of BI/reporting architecture, semantic modeling, and analytics performance optimization.

Benefits / Compensation

The compensation range for this role is specific to Washington, DC, and takes into account a wide range of factors including but not limited to the skill sets required/preferred; prior experience and training; licenses and/or certifications. The anticipated base salary range for this role is $150,000 to $170,000.

In addition to the base salary, the hired professional will enjoy a comprehensive benefits package spanning retirement benefits, health insurance, life insurance and disability, paid time off, paid holidays, family planning benefits and various wellness programs. Additionally, the hired professional may also be eligible to participate in an annual discretionary incentive program, the award of which will be dependent on various factors, including, without limitation, individual and organizational performance.