Business Intelligence Engineer

What You'll Do:

• Maintain the BI Snowflake environment: schemas, roles and access, performance tuning, warehouse sizing, and cost monitoring 

• Build and optimize Power BI semantic models and dashboards (star schemas, DAX measures, row-level security), tuning DirectQuery and Import models against Snowflake 

• Translate business requirements, KPIs, and metric definitions into technical designs. 

• Set engineering standards for naming, code review, CI/CD, and documentation 

• Partner with the integrations team to define what the BI platform needs from landed data and resolve upstream issues 

• Own data quality in the transformation layer: testing, monitoring, reconciliation, and root-cause analysis 

• Write complex, performant SQL to model, transform, and validate data 

• Develop and maintain dbt models (staging, intermediate, marts) with tests, documentation, and version control 

• Set up and tune Snowflake Cortex Analyst and Semantic Views so natural-language questions return accurate answers 

• Evaluate, test, and pilot AI-enabled analytics, such as natural language querying over semantic models, AI-generated commentary, and automated variance explanation. 

• Mentor analysts and stakeholders on data models and self-service 

• Pitch in with PowerBI report and dashboard builds when needed.

What You'll Bring:

• 5+ years in data engineering, analytics engineering, or BI engineering 

• Bachelor’s degree in Finance, IT, Information Systems, Engineering, or a related field (or equivalent experience) 

• Advanced SQL and dbt, with a solid grasp of dimensional modeling and data warehousing concepts 

• Deep hands-on Snowflake experience, including performance tuning, access control, and cost management 

• Strong Power BI skills, including DAX, data modeling, and publishing and managing workspaces 

• Git and CI/CD experience for analytics code 

• Working fluency with AI tools in analytics or engineering work, with sound judgment about their limits, including inaccurate or ungrounded answers 

• Clear communication with technical and non-technical audiences, and the ability to translate business needs into technical requirements and carry them through to deployment with strong attention to detail

Preferred Qualifications:

• Experience building ELT pipelines and data ingestion (Fivetran or similar, including API-based sources) 

• Python for scripting and automation 

• Experience with orchestration tools (Airflow, Dagster, or similar) 

• Infrastructure-as-code experience (Terraform or similar) for Snowflake 

• Hands-on experience with Snowflake Cortex Analyst, semantic views, or similar natural-language-to-SQL tools 

• Familiarity with data governance, cataloging, and lineage tooling 

• Background in finance, FP&A, or sales analytics 

• Exposure to Tableau or other BI tools