Business Intelligence Engineer

This role sits at the intersection of data engineering and business intelligence — approximately 60% backend data infrastructure and 40% BI and reporting. The right candidate is strong on both sides, not specialized in one.

• Serve as the primary operator of the GCP data environment: BigQuery, Cloud Functions, Cloud Scheduler, and Cloud Storage, in close partnership with IT on security and access
• Write and maintain Python-based ETL pipelines pulling from source platforms (Toggl, Rippling, Xero, Salesforce, and others) and landing data in BigQuery
• Extend the pipeline portfolio to bring new data sources online and unlock reporting capabilities that do not currently exist
• Automate recurring operational workflows currently running manually or locally: scheduled data quality checks, automated exports, and replacing one-off scripts with reliable GCP functions
• Own the full Tableau dashboard portfolio across all internal teams: data connections, SQL, refresh schedules, QC, documentation, and bug resolution
• Build net-new dashboards for audiences that don't have reliable reporting today, including executive, director, and operational views covering project financials, service line performance, and renewal visibility
• Own data integrity within the analytics layer: diagnose whether issues are pipeline problems, dashboard logic problems, or source data issues, and route accordingly
• Maintain naming conventions, schema documentation, and dataset organization in BigQuery
• Be the first point of contact when a dashboard breaks or a pipeline fails — own resolution, not just escalation
• Partner with stakeholders across Business Operations, Finance, People & Talent, Sales, and IT to translate business needs into working data solutions
  
  Requirements
• 5+ years of experience in Business Intelligence, Analytics Engineering, Data Engineering, or a hybrid of both
• Hands-on GCP experience: BigQuery (primary), Cloud Functions, Cloud Scheduler, and Cloud Storage
• Strong Python development experience building and maintaining ETL pipelines; must write Python regularly, not occasionally
• Advanced SQL skills with experience querying cloud data warehouses and troubleshooting data quality issues
• Tableau proficiency: has built dashboards from scratch, not just consumed or made minor modifications to existing ones
• Experience maintaining production reporting environments and troubleshooting data pipelines end-to-end
• Familiarity with Git/GitHub version control workflows
• Strong ability to diagnose data problems across pipeline, dashboard, and source system layers independently
• Strong communication skills: able to explain technical data concepts to non-technical stakeholders across multiple business functions
• Experience using AI-assisted development tools (Claude Code, GitHub Copilot, Cursor, Codex, or similar)
• English at B2 level or above; must be able to communicate clearly in a professional English-speaking environment

Preferred Qualifications

• Background in professional services, consulting, accounting, legal, engineering, or similar project-based organizations
• Experience at companies with 100-500 employees: understands the data needs of a mid-size professional services organization (too small = insufficient complexity; too large = too specialized)
• Azure experience
• Data modeling and analytics engineering best practices (dbt, dimensional modeling, or equivalent)
• Experience supporting executive and director-level reporting and operational analytics

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