Business Intelligence Engineer at Sur

Worldwide

<p>As a Business Intelligence Engineer, you will take full ownership of a data and reporting ecosystem that has been built but never had a dedicated owner. The infrastructure is in place — Google Cloud pipelines, a Tableau dashboard portfolio, and integrations across the company's core platforms — and the business has outgrown the model of splitting this responsibility across people with other priorities.</p><p>You will inherit this ecosystem, assess it, stabilize it, and then extend it. You will be the primary day-to-day operator of GCP data infrastructure, the sole owner of the internal Tableau environment, and the person who makes sure leadership across Operations, Finance, People &amp; Talent, and Sales has accurate, timely data to make decisions.</p><p>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.</p><p></p><ul><li>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</li><li>Write and maintain Python-based ETL pipelines pulling from source platforms (Toggl, Rippling, Xero, Salesforce, and others) and landing data in BigQuery</li><li>Extend the pipeline portfolio to bring new data sources online and unlock reporting capabilities that do not currently exist</li><li>Automate recurring operational workflows currently running manually or locally: scheduled data quality checks, automated exports, and replacing one-off scripts with reliable GCP functions</li><li>Own the full Tableau dashboard portfolio across all internal teams: data connections, SQL, refresh schedules, QC, documentation, and bug resolution</li><li>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</li><li>Own data integrity within the analytics layer: diagnose whether issues are pipeline problems, dashboard logic problems, or source data issues, and route accordingly</li><li>Maintain naming conventions, schema documentation, and dataset organization in BigQuery</li><li>Be the first point of contact when a dashboard breaks or a pipeline fails — own resolution, not just escalation</li><li>Partner with stakeholders across Business Operations, Finance, People &amp; Talent, Sales, and IT to translate business needs into working data solutions</li></ul> <ul><li>5+ years of experience in Business Intelligence, Analytics Engineering, Data Engineering, or a hybrid of both</li><li>Hands-on GCP experience: BigQuery (primary), Cloud Functions, Cloud Scheduler, and Cloud Storage </li><li>Strong Python development experience building and maintaining ETL pipelines; must write Python regularly, not occasionally</li><li>Advanced SQL skills with experience querying cloud data warehouses and troubleshooting data quality issues</li><li>Tableau proficiency: has built dashboards from scratch, not just consumed or made minor modifications to existing ones</li><li>Experience maintaining production reporting environments and troubleshooting data pipelines end-to-end</li><li>Familiarity with Git/GitHub version control workflows</li><li>Strong ability to diagnose data problems across pipeline, dashboard, and source system layers independently</li><li>Strong communication skills: able to explain technical data concepts to non-technical stakeholders across multiple business functions</li><li>Experience using AI-assisted development tools (Claude Code, GitHub Copilot, Cursor, Codex, or similar) </li><li>English at B2 level or above; must be able to communicate clearly in a professional English-speaking environment</li></ul><p> </p><p>Preferred Qualifications</p><ul><li>Background in professional services, consulting, accounting, legal, engineering, or similar project-based organizations</li><li>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)</li><li>Azure experience </li><li>Data modeling and analytics engineering best practices (dbt, dimensional modeling, or equivalent)</li><li> Experience supporting executive and director-level reporting and operational analytics</li></ul> <p>Salary: $4,000 USD per month</p><p>PTO: Unlimited PTO</p>