Data Engineer

Role overview

What you will do

• Advise clients on standardizing data structures, quality, and reuse; lead ETL from customer ERP systems into MindBridge.
• Understand ERP financial data models, automate complex ETL jobs, and extract, format, and shape financial data.
• Troubleshoot data issues and provide workarounds and permanent fixes.
• Maintain templates and documentation for requirements, processes, flow diagrams, and mappings.
• Design pipelines for analytics, management reports, and dashboards; serve as the data ingestion product expert.
• Provide customer-informed product feedback and collaborate with customer success, support, product, development, and data science.
• Contribute data expertise to roadmap discussions and ensure feature additions receive software or release testing when required.

What you bring

• Comfort manipulating datasets with Python and creating API requests.
• Proficiency with Microsoft Excel, Python, SQL, and project management software.
• Positive, detail-oriented, self-motivated, team-oriented approach; strong interpersonal communication and customer experience focus.
• Ability to adapt, reprioritize in a fast-paced environment, and support occasional client needs outside normal business hours.
• May be required to travel to the US, UK, and EU.

Desired education and experience

• A computer science, accounting, or business degree, or equivalent experience, is required.
• Desired: 5+ years using SQL and Python to build and shape structured or semi-structured datasets.
• Desired: 5+ years of project work and advanced experience with ETL, data lakes, analysis, profiling, mapping, modeling, and analytics.
• Desired: 5+ years in customer service, consulting, or support at a software or technology company, and 5+ years with ERP systems such as Oracle, NetSuite, Sage, or SAP.
• Desired: proficiency with Excel VBA and macros; accounting or audit experience is a strong asset.

Compensation

• Expected base salary is CAD 90,000 to CAD 110,000, with possible bonus awards; placement depends on location, skills, experience, and qualifications.

Workplace

• Flexible work is described as hybrid or remote; the posting does not specify which arrangement applies to this role.

Employment contingency