BambooHR is seeking a Sr. Data Engineer to design, build, and operate scalable data platforms, analytics systems, and AI/ML infrastructure.

Requirements

Collaborate with data analysts, data scientists, ML engineers, software engineers, and business stakeholders
Design, develop, and maintain scalable data ingestion and transformation pipelines
Build and optimize data lake, lakehouse, warehouse, and data mart architectures
Develop and maintain data models including facts, dimensions, feature datasets, and domain-specific data products
Translate business requirements into design documents
Design and manage cloud-based data and ML infrastructure
Design, build, and operationalize machine learning pipelines
Support ML model lifecycle management
Develop and maintain ML feature stores and reusable feature pipelines
Build and integrate AI-powered applications and agentic workflows
Design and implement data pipelines for AI systems
Develop and maintain unit, integration, and data quality tests
Participate in peer code reviews, pull requests, and team coding standards
Document data pipelines, ML pipelines, models, infrastructure, and standard operating procedures
Define infrastructure as code and support CI/CD pipelines for data and ML systems
Ensure data privacy, security, and access control best practices
Identify and implement improvements in efficiency, scalability, resilience, and performance
Contribute to evolving data, ML, and AI platform architecture, tools, and best practices

Benefits

BambooHR is seeking a Sr. Data Engineer to design, build, and operate scalable data platforms, analytics systems, and AI/ML infrastructure.

Collaborate with data analysts, data scientists, ML engineers, software engineers, and business stakeholders
Design, develop, and maintain scalable data ingestion and transformation pipelines
Build and optimize data lake, lakehouse, warehouse, and data mart architectures
Develop and maintain data models including facts, dimensions, feature datasets, and domain-specific data products
Translate business requirements into design documents
Design and manage cloud-based data and ML infrastructure
Design, build, and operationalize machine learning pipelines
Support ML model lifecycle management
Develop and maintain ML feature stores and reusable feature pipelines
Build and integrate AI-powered applications and agentic workflows
Design and implement data pipelines for AI systems
Develop and maintain unit, integration, and data quality tests
Participate in peer code reviews, pull requests, and team coding standards
Document data pipelines, ML pipelines, models, infrastructure, and standard operating procedures
Define infrastructure as code and support CI/CD pipelines for data and ML systems
Ensure data privacy, security, and access control best practices
Identify and implement improvements in efficiency, scalability, resilience, and performance
Contribute to evolving data, ML, and AI platform architecture, tools, and best practices