Business Intelligence Engineer

CrossCountry Consulting

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

Posted 11/6/2026full-timeUnited StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in maintaining and optimizing Snowflake environments, building Power BI dashboards, and translating business requirements into technical designs. Proficient in SQL, dbt, and data modeling, with a strong focus on data quality and governance.

Highest-signal resume keywords

Snowflake Performance TuningAdvanced SQLPower BI Data ModelingDbt DevelopmentData Governance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLDbtDAXDimensional ModelingData WarehousingData TransformationELT PipelinesPythonInfrastructure-as-CodeNatural-Language Querying

Soft Skills

Clear CommunicationAttention to DetailMentoring

Tools & Technologies

Power BISnowflakeFivetranAirflowGitCI/CDTerraformTableau

Industry Keywords

FinanceAnalytics EngineeringBI EngineeringSales AnalyticsData Governance

Tech Stack

Tools & technologies

AirflowPythonSnowflakeSQLTableauTerraform

About the role

Key responsibilities & impact

Maintain the BI Snowflake environment, including schemas, roles and access, performance tuning, warehouse sizing, and cost monitoring
Build and optimize Power BI semantic models and dashboards using star schemas, DAX measures, row-level security, and 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 BI platform requirements for landed data and resolve upstream issues
Own data quality in the transformation layer through testing, monitoring, reconciliation, and root-cause analysis
Write complex, performant SQL to model, transform, and validate data
Develop and maintain dbt staging, intermediate, and mart models with tests, documentation, and version control
Set up and tune Snowflake Cortex Analyst and Semantic Views for accurate natural-language query responses
Evaluate, test, and pilot AI-enabled analytics, including natural-language querying, AI-generated commentary, and automated variance explanation
Mentor analysts and stakeholders on data models and self-service
Build Power BI reports and dashboards when needed
Build and maintain the transformation layer, data models, and Snowflake environment behind reporting
Partner with finance, sales, and operations leaders to define metrics and deliver trusted end-to-end reporting

Requirements

What you’ll need

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
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
Clear communication with technical and non-technical audiences
Ability to translate business needs into technical requirements and carry them through to deployment with strong attention to detail
Experience building ELT pipelines and data ingestion, including Fivetran or similar and API-based sources
Python for scripting and automation
Experience with orchestration tools such as Airflow or Dagster
Infrastructure-as-code experience, such as Terraform, 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

Benefits

Comp & perks

Comprehensive healthcare options, including medical, dental, and vision coverage
Flexible spending accounts
401(k) with company matching
Generous parental and maternity leave policies
Technology stipends
Wellness reimbursement programs
Equal employment opportunities and compliance with applicable pay transparency and labor laws