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 $160,000 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.
Due to the high volume of candidates, please be advised that only candidates selected to interview will be contacted by Carlyle.
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 $160,000 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.
Due to the high volume of candidates, please be advised that only candidates selected to interview will be contacted by Carlyle.