National Philanthropic Trust
BI Engineer
ABOUT NATIONAL PHILANTHROPIC TRUST
National Philanthropic Trust is a public charity dedicated to providing philanthropic expertise to donors, foundations, and financial institutions, enabling them to realize their philanthropic aspirations. NPT was founded in 1996. Since that time, we have raised more than $80.2 billion in charitable contributions and currently manage $57.1 billion in charitable assets. We have made more than 930,000 grants totaling more than $37.7 billion to charities all over the world. We rank among the largest grantmaking institutions in the United States.
Our mission is to increase philanthropy in society. To that end, our experienced staff of philanthropic professionals are fully prepared to help you establish and administer your donor-advised fund. NPT is led by a Board of Trustees composed of nationally known experts in philanthropy and business.
At National Philanthropic Trust, we foster a welcoming environment for all.People are valued and respected for who they are-with opportunities to bring theirentrepreneurial spirit andtalents to increase giving around the world. We have an inclusive, supportive, collaborative culture that makes National Philanthropic Trust one of the most rewarding places to work.
Job Summary:
The BI Engineer will play a pivotal role in NPT's data transformation through the implementation and management of our enterprise data warehouse and business intelligence platforms. This technical position bridges data engineering expertise with business intelligence capabilities to create scalable data solutions that enhance organization-wide decision-making. The role will be responsible for designing and implementing data pipelines, creating dimensional models, and maintaining critical business intelligence reports while supporting the transition to a modern cloud data warehouse architecture. The ideal candidate will combine strong technical skills with business acumen to deliver insights that drive strategic decisions.
Salary range is $75,000 - $85,000 plus 9.6% annual discretionary bonus
Primary Functions and Essential Responsibilities:
Data Engineering & Warehouse Implementation (50%)
Collaborate with external implementation partners on data warehouse architecture design and deployment
Serve as the internal technical expert and primary liaison during data warehouse implementation projects
Design and validate data pipelines using modern cloud data warehouse platforms for ETL/ELT processes
Lead the transition to becoming the long-term technical owner of the data warehouse platform post-implementation
Create and optimize dimensional data models aligned with business reporting needs
Implement medallion architecture to ensure appropriate data quality and processing tiers
Develop data mart structures that support both standard reporting and ad-hoc analysis
Establish data quality monitoring processes and automated testing to ensure integrity across systems
Support data integration between enterprise systems and the data warehouse
Implement data documentation, cataloging, and lineage tracking to enhance discoverability and governance
Design and maintain robust data transformation logic for business rule implementation
Absorb knowledge transfer from external partners to ensure internal expertise and platform ownership
Business Intelligence Development (30%)
Maintain and enhance critical PowerBI dashboards and reports that support business operations
Create standardized data models and visualization patterns that promote consistency across the organization
Develop complex DAX measures and calculations for advanced analytics and KPI development
Implement row-level security and appropriate access controls for sensitive data
Design self-service analytics capabilities to reduce dependency on custom report development
Create training materials and documentation for business users and power users
Optimize report performance through query tuning, data model optimization, and best practice implementation
Support migration of existing reports to new data warehouse architecture
Technical Collaboration & Project Support (20%)
Partner with business stakeholders to translate requirements into technical data warehouse specifications
Coordinate with external consultants and implementation partners on data warehouse projects, serving as NPT's technical representative
Lead knowledge transfer sessions and documentation from external partners to ensure internal ownership
Support data governance initiatives through technical implementation and platform management
Provide SQL expertise and data modeling guidance for complex analytical requirements
Assist with planning and implementing data migrations from legacy systems to modern platforms
Contribute to the development of data standards, naming conventions, and architectural best practices
Collaborate with application development teams on data integration requirements and API specifications
The above list is not exhaustive, additional tasks may be assigned as necessary but are not a major function of the position.
Qualifications :
Education/Certification:
Bachelor's degree in Computer Science, Information Technology, Data Science, Data Engineering, or related field
Experience:
3+ years of experience in data engineering, data warehousing, or business intelligence development
Experience working in Agile/Scrum environments
Experience leveraging Microsoft Fabric architecture and components as an analytics layer, including centralized semantic models, self-service analytics, report versioning & pipelines, and integration with external data platforms
Required Technical Skillsets
Strong SQL skills for complex query development, optimization, and data transformation
Experience with SQL Server Integration Services (SSIS) for ETL processes and data movement
Experience with cloud data warehouse platforms (Azure Synapse or similar modern platforms)
Proven experience designing and implementing dimensional data models for reporting and analytics
Experience with modern data pipeline development and orchestration tools
Understanding of data warehousing concepts including ETL/ELT processes, medallion architecture, slowly changing dimensions, and fact/dimension modeling
Experience with business intelligence tools, particularly PowerBI development and administration
Familiarity with data governance principles, data quality frameworks, and best practices
Preferred Technical Skillsets
Experience with Snowflake or other modern cloud data warehouse implementations
SQL Server database administration experience including performance tuning, indexing, and maintenance
Knowledge of medallion architecture patterns and implementation across various data platforms
Advanced PowerBI certification or demonstrated expertise in complex dashboard development
Experience with data orchestration tools (Apache Airflow, Azure Data Factory, dbt, or similar)
Experience with modern ELT platforms (Fivetran, Matillion, Rivery) or other cloud-native data integration tools
Programming skills in Python for data processing, analysis, and machine learning workflows
Experience with data science libraries (pandas, numpy, scikit-learn) and machine learning model development
Experience with version control, CI/CD practices, and DataOps methodologies
Familiarity with customer relationship management and financial services data models
Experience with data migration projects and legacy system modernization
Knowledge of data security, privacy regulations, and compliance frameworks
Exposure to machine learning, predictive analytics, and AI implementation in business intelligence contexts
Experience with advanced statistical analysis and data science methodologies
Knowledge, Skills and Abilities:
Strong analytical mindset with exceptional attention to detail and data accuracy
Excellent problem-solving abilities and capacity to work with complex, interconnected systems
Effective communication skills for both technical and business audiences, with ability to translate technical concepts
Self-motivated with ability to work independently while collaborating effectively in small, agile team environments
Comfortable taking on diverse responsibilities and wearing multiple hats in a lean team structure
Passion for continuous learning and adapting to rapidly evolving data technologies and platforms
Ability to manage multiple priorities in a dynamic environment while maintaining high quality standards
Strong organizational skills and project management capabilities for complex technical implementations
Collaborative mindset with ability to work closely with external partners while maintaining internal ownership
Technical Environment:
This role will work with NPT's evolving data technology stack including:
Data Warehouse Platforms : Modern cloud data warehouse (implementation in progress)
Business Intelligence:
PowerBI, data visualization and self-service analytics tools
Data Integration:
ETL/ELT tools, API integrations, data pipeline orchestration platforms
Databases:
SQL Server, cloud-based data solutions, data lake storage
Cloud Services:
Microsoft Azure and associated data services
Data Governance:
Data cataloging, quality monitoring, and lineage tracking tools
ABOUT NATIONAL PHILANTHROPIC TRUST
National Philanthropic Trust is a public charity dedicated to providing philanthropic expertise to donors, foundations, and financial institutions, enabling them to realize their philanthropic aspirations. NPT was founded in 1996. Since that time, we have raised more than $80.2 billion in charitable contributions and currently manage $57.1 billion in charitable assets. We have made more than 930,000 grants totaling more than $37.7 billion to charities all over the world. We rank among the largest grantmaking institutions in the United States.
Our mission is to increase philanthropy in society. To that end, our experienced staff of philanthropic professionals are fully prepared to help you establish and administer your donor-advised fund. NPT is led by a Board of Trustees composed of nationally known experts in philanthropy and business.
At National Philanthropic Trust, we foster a welcoming environment for all.People are valued and respected for who they are-with opportunities to bring theirentrepreneurial spirit andtalents to increase giving around the world. We have an inclusive, supportive, collaborative culture that makes National Philanthropic Trust one of the most rewarding places to work.
Job Summary:
The BI Engineer will play a pivotal role in NPT's data transformation through the implementation and management of our enterprise data warehouse and business intelligence platforms. This technical position bridges data engineering expertise with business intelligence capabilities to create scalable data solutions that enhance organization-wide decision-making. The role will be responsible for designing and implementing data pipelines, creating dimensional models, and maintaining critical business intelligence reports while supporting the transition to a modern cloud data warehouse architecture. The ideal candidate will combine strong technical skills with business acumen to deliver insights that drive strategic decisions.
Salary range is $75,000 - $85,000 plus 9.6% annual discretionary bonus
Primary Functions and Essential Responsibilities:
Data Engineering & Warehouse Implementation (50%)
Collaborate with external implementation partners on data warehouse architecture design and deployment
Serve as the internal technical expert and primary liaison during data warehouse implementation projects
Design and validate data pipelines using modern cloud data warehouse platforms for ETL/ELT processes
Lead the transition to becoming the long-term technical owner of the data warehouse platform post-implementation
Create and optimize dimensional data models aligned with business reporting needs
Implement medallion architecture to ensure appropriate data quality and processing tiers
Develop data mart structures that support both standard reporting and ad-hoc analysis
Establish data quality monitoring processes and automated testing to ensure integrity across systems
Support data integration between enterprise systems and the data warehouse
Implement data documentation, cataloging, and lineage tracking to enhance discoverability and governance
Design and maintain robust data transformation logic for business rule implementation
Absorb knowledge transfer from external partners to ensure internal expertise and platform ownership
Business Intelligence Development (30%)
Maintain and enhance critical PowerBI dashboards and reports that support business operations
Create standardized data models and visualization patterns that promote consistency across the organization
Develop complex DAX measures and calculations for advanced analytics and KPI development
Implement row-level security and appropriate access controls for sensitive data
Design self-service analytics capabilities to reduce dependency on custom report development
Create training materials and documentation for business users and power users
Optimize report performance through query tuning, data model optimization, and best practice implementation
Support migration of existing reports to new data warehouse architecture
Technical Collaboration & Project Support (20%)
Partner with business stakeholders to translate requirements into technical data warehouse specifications
Coordinate with external consultants and implementation partners on data warehouse projects, serving as NPT's technical representative
Lead knowledge transfer sessions and documentation from external partners to ensure internal ownership
Support data governance initiatives through technical implementation and platform management
Provide SQL expertise and data modeling guidance for complex analytical requirements
Assist with planning and implementing data migrations from legacy systems to modern platforms
Contribute to the development of data standards, naming conventions, and architectural best practices
Collaborate with application development teams on data integration requirements and API specifications
The above list is not exhaustive, additional tasks may be assigned as necessary but are not a major function of the position.
Qualifications :
Education/Certification:
Bachelor's degree in Computer Science, Information Technology, Data Science, Data Engineering, or related field
Experience:
3+ years of experience in data engineering, data warehousing, or business intelligence development
Experience working in Agile/Scrum environments
Experience leveraging Microsoft Fabric architecture and components as an analytics layer, including centralized semantic models, self-service analytics, report versioning & pipelines, and integration with external data platforms
Required Technical Skillsets
Strong SQL skills for complex query development, optimization, and data transformation
Experience with SQL Server Integration Services (SSIS) for ETL processes and data movement
Experience with cloud data warehouse platforms (Azure Synapse or similar modern platforms)
Proven experience designing and implementing dimensional data models for reporting and analytics
Experience with modern data pipeline development and orchestration tools
Understanding of data warehousing concepts including ETL/ELT processes, medallion architecture, slowly changing dimensions, and fact/dimension modeling
Experience with business intelligence tools, particularly PowerBI development and administration
Familiarity with data governance principles, data quality frameworks, and best practices
Preferred Technical Skillsets
Experience with Snowflake or other modern cloud data warehouse implementations
SQL Server database administration experience including performance tuning, indexing, and maintenance
Knowledge of medallion architecture patterns and implementation across various data platforms
Advanced PowerBI certification or demonstrated expertise in complex dashboard development
Experience with data orchestration tools (Apache Airflow, Azure Data Factory, dbt, or similar)
Experience with modern ELT platforms (Fivetran, Matillion, Rivery) or other cloud-native data integration tools
Programming skills in Python for data processing, analysis, and machine learning workflows
Experience with data science libraries (pandas, numpy, scikit-learn) and machine learning model development
Experience with version control, CI/CD practices, and DataOps methodologies
Familiarity with customer relationship management and financial services data models
Experience with data migration projects and legacy system modernization
Knowledge of data security, privacy regulations, and compliance frameworks
Exposure to machine learning, predictive analytics, and AI implementation in business intelligence contexts
Experience with advanced statistical analysis and data science methodologies
Knowledge, Skills and Abilities:
Strong analytical mindset with exceptional attention to detail and data accuracy
Excellent problem-solving abilities and capacity to work with complex, interconnected systems
Effective communication skills for both technical and business audiences, with ability to translate technical concepts
Self-motivated with ability to work independently while collaborating effectively in small, agile team environments
Comfortable taking on diverse responsibilities and wearing multiple hats in a lean team structure
Passion for continuous learning and adapting to rapidly evolving data technologies and platforms
Ability to manage multiple priorities in a dynamic environment while maintaining high quality standards
Strong organizational skills and project management capabilities for complex technical implementations
Collaborative mindset with ability to work closely with external partners while maintaining internal ownership
Technical Environment:
This role will work with NPT's evolving data technology stack including:
Data Warehouse Platforms : Modern cloud data warehouse (implementation in progress)
Business Intelligence:
PowerBI, data visualization and self-service analytics tools
Data Integration:
ETL/ELT tools, API integrations, data pipeline orchestration platforms
Databases:
SQL Server, cloud-based data solutions, data lake storage
Cloud Services:
Microsoft Azure and associated data services
Data Governance:
Data cataloging, quality monitoring, and lineage tracking tools