About this role
About the position
Maxa AI has solved the hard technical problem: transforming fragmented ERP data into CFO-trusted insights in weeks instead of months. We have the product, methodology and the technology. What we need is an Analytics Engineer who owns the technical heart of our delivery process, and who seeks to blend data engineering, analytics engineering, and software development responsibilities. This is not a standard dbt shop role. You will work directly with customers during structured discovery workshops, validate detailed technical specifications with cross-functional partners, build data models that span dimensions, hierarchies, measures, and event timelines, and contribute to a shared pattern library that compounds our delivery intelligence with every engagement. And here’s where it gets even more interesting: we’re building an AI-augmented data engineering platform. As an AE at Maxa, your role will evolve from writing SQL to teaching AI agents to build out data models. From building pipelines to architecting the system that builds pipelines. Every intervention you make today becomes training data for tomorrow’s automation.
Responsibilities
• Translate validated technical specifications into a unified business data model: using dbt on Snowflake.
• Ensuring robust data infrastructure and delivering actionable insights to business stakeholders.
• Optimizing SQL queries in Snowflake to maximize performance.
• Participate in technical specification walkthroughs with Business Analysts and Business Data Analysts, validating feasibility and completeness before development begins.
• Implement and validate business rules: harmonization logic, metric calculations, and exception handling.
• Contributing to the continuous improvement of our proprietary data model.
• Working closely with our cross-functional teams: Delivery Managers, Business Analysts, Business Data Analysts, Business Intelligence.
• Capture reusable patterns in our shared library: entity definitions, event flows, common ERP table mappings, and resolution heuristics from past engagements.
• Experiment boldly with AI and automation and find the workflows that 10x delivery speed.
• Obsess over the metrics that matter: cycle time per entity, first-pass quality rate, control total accuracy, pattern library reuse rate.
Requirements
• 3-5 years of experience in data modeling, serving business purposes (ERP systems experience is a great asset!)
• Master dbt and are passionate about its possibilities.
• Strong with SQL and Git, and knowledgeable about Python
• Deep understanding of software development best practices
• Can bridge the gap between business needs and technical solutions
• Communicate proactively, in both English and French
• Curious and not afraid to test new approaches
Nice-to-haves
• Event sourcing or temporal modeling: You’ve worked with immutable event logs, change data capture, slowly changing dimensions, or similar patterns and understand why they matter for auditability and time-series analysis.
• AI/LLM curiosity in practice: You’ve experimented with AI-assisted development, prompt engineering, or agentic workflows, not just talked about it.
• You translate in both directions flawlessly: C-level language → technical specs, AND technical constraints → business implications
• You obsess over operational excellence: you see patterns across projects and ask "how do we standardize this?"
Benefits
• Competitive base salary (aligned to seniority; this is a newly created role)
• 4 weeks vacation year one, 5 weeks thereafter
• RRSP contribution after 3 months
• On-site chef: three-course lunches for \$12
• Stock options in a post–Series A high-growth AI company
• Define delivery standards for enterprise AI