Data Solutions Engineer
On-site · Vancouver, British Columbia, Canada
Job Summary
Own reconciliation of customer data across systems: pull a clean customer list from the backend into the CRM with no duplicates or ghost accounts, audit HubSpot data, and decide what stays, is cleaned, or automated. Build a live two-way integration between HubSpot and the backend to enable automatic data flows and trigger actions. Establish a single trusted place to generate sales pipeline, retention, customer health, and other GTM reporting. Run customer onboarding data-mapping sessions directly with labs. Deliver an engineering brief detailing friction points and fixes to enable labs to complete mappings independently. Coordinate with Customer Success on onboarding and with our HubSpot partner on integration. Grow the data foundation to scale onboarding as a repeatable process and ensure data trust across systems. Role emphasizes end-to-end data engineering, cleansing, integration, sync logic, and reporting architecture.
Required Qualifications
- Bachelor's degree in Statistics, Computer Science, Data Science, Economics, or a related field
- 4–5 years of professional experience in data analysis, data engineering, or solutions/implementation engineering
- Advanced SQL skills (joins, CTEs, window functions, subqueries)
- Proficiency in Python for data analysis and workflow automation
- Experience with ETL/ELT pipelines and workflow automation
- Hands-on CRM data experience — auditing, cleansing, deduplication, and data migration. HubSpot strongly preferred
- Systems integration experience — building or maintaining two-way integrations between platforms (APIs, middleware, sync logic)
- Familiarity with Git/GitHub for version control and collaboration
- Comfortable running customer-facing working sessions and explaining data configuration to non-technical users
- Able to translate customer friction into clear, actionable briefs for engineering
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