Sr Business Intelligence Engineer

We are seeking a highly skilled Senior BI Engineer to take ownership of our Snowflake data platform and help evolve it into a scalable, well-governed foundation for analytics and AI. This is a hands-on engineering role responsible for shaping data architecture, enforcing standards, and building a clean, reliable data layer that supports both business intelligence and AI-driven use cases. You will report directly to the Director of BI and have significant autonomy in how the platform evolves. 

Own and Elevate the Data Platform 

• →Own the design and evolution of our Snowflake data platform end-to-end 
• →Refactor and enhance pipelines, dbt models, and transformations to meet high standards for scalability, performance, and maintainability 
• →Make and drive architectural decisions—not just implement tasks 

Architect for Scale and Clarity 

• →Implement and enforce medallion architecture (bronze/silver/gold) with clear separation of concerns 
• →Design and build dimensional models (star schemas) that are intuitive, performant, and durable 
• →Implement SCD Type 2 and other core warehousing patterns correctly and consistently 
• →Establish and enforce standards for schemas, naming, and data contracts 
• →Integrate and normalize data from a wide range of source systems (SaaS apps, operational databases, event streams, finance/CRM tools) into a coherent, well-modeled warehouse layer 

Build an AI-Ready Data Layer 

• →Design data models optimized for semantic clarity and AI/LLM consumption 
• →Implement semantic views in Snowflake to enable tools like Claude via MCP 
• →Ensure data is traceable, explainable, and trustworthy 

Establish a Real Data Engineering SDLC 

• →Implement a Git-driven development lifecycle (branching, PR reviews, testing, deployments) 
• →Introduce and enforce: 
• →Data quality testing and validation 
• →Schema enforcement and regression safeguards 
• →Clear promotion paths from dev → prod 
• →Raise the bar on engineering discipline across the data function 

Leverage AI as a Force Multiplier 

• →Use AI tools to accelerate development while maintaining high standards 
• →Guide and validate AI-generated code—never blindly trust it 
• →Explore agent-based approaches for: 
• →Data quality auditing 
• →Pipeline validation 
• →Anomaly detection and monitoring 

Collaborate and Lead Technically 

• →Partner with BI analysts to deliver reliable, well-modeled datasets (Power BI downstream) 
• →Translate ambiguous business requirements into clean, scalable data models 
• →Provide technical direction to a supporting QA/offshore resource (planned) 

Documentation & Transparency 

• →Build a culture of clear documentation, lineage, and data discoverability 
• →Ensure systems are understandable and maintainable by others 
• →Other duties as assigned 

Data Engineering Depth & Ownership 

• 5+ years of hands-on data engineering experience, with a meaningful portion spent owning architecture and driving development — not just executing assigned tasks 
• Strong experience with Snowflake as a primary warehouse 
• Advanced SQL skills and experience building production-grade ELT pipelines 
• Strong hands-on experience with dbt for modeling, testing, and transformation — including macros, tests, snapshots, and managing a production dbt project at scale 
• Experience integrating and normalizing data from many disparate source systems — SaaS APIs, application databases, CRM/ERP, finance systems, event data — into consistent, analytics-ready models 
• Deep, hands-on experience with: 
• Star schemas and dimensional modeling 
• SCD Type 2 implementations 
• Layered/medallion architectures 
• Ability to make tradeoffs and defend decisions (performance vs flexibility, normalization vs usability, etc.) 
• Track record of improving data quality, consistency, and trust 
• Experience implementing Git-based workflows and structured SDLC practices for data 
• Strong instincts around testing, governance, and maintainability 
• Comfortable setting and enforcing standards across a team 

AI-First Mindset

• Demonstrated ability to use AI tools to meaningfully increase output and velocity 
• Strong judgment to validate and refine AI-generated work 
• Interest in applying AI/agents to improve data engineering workflows 

• Familiarity with Power BI 
• Familiarity with Salesforce as a data source (objects, schema, Salesforce-to-warehouse pipelines) 
• Experience working with or leading offshore/support resources

• →The People! 
• →90% healthcare premiums company covered 
• →HSA company contribution 
• →401K match at 4% with immediate vesting 
• →Flexible PTO (typically 3 to 4 weeks a year) 
• →10 paid holidays 
• →Monthly contributions for life activities & wellness 
• →Access to LinkedIn learning with monthly dedicated time to explore