Data Engineer – Data Platform (AI-Enabled)

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Engineer – Data Platform (AI-Enabled) based in Canada.

This role offers the opportunity to help build a modern data platform designed for both human users and AI systems. You’ll combine strong data engineering fundamentals with practical, hands-on use of AI to accelerate development, improve quality, and create greater engineering leverage. Working within a small platform team, you’ll build trusted, governed, and semantically rich data products that support customers, product teams, engineering, BI, and business users. You’ll contribute to semantic modeling and self-service analytics while developing reusable platform capabilities rather than isolated solutions. The role also involves helping teammates adopt AI-first development practices through coaching, experimentation, and leading by example. With ownership extending into production operations, you’ll have a direct impact on the reliability, scalability, and AI readiness of the organization’s data ecosystem.

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Accountabilities:

• Build and maintain trusted, well-modeled, production-grade data products supporting customers, product and engineering teams, and internal business users.

• Partner with product, engineering, customer-facing teams, and business stakeholders to understand data needs and translate them into scalable platform capabilities.

• Help design and implement a semantic layer that provides consistent business definitions, metrics, and data models for humans, BI tools, and AI systems.

• Support a federated BI approach that enables platform consumers to safely and independently develop insights and analytics.

• Use AI tools as an integral part of daily engineering work, including development, testing, documentation, debugging, analysis, design, and problem-solving.

• Establish and promote practical AI-first development patterns that increase productivity while maintaining engineering quality, security, governance, and trust.

• Develop reusable data engineering capabilities across pipelines, integrations, testing, documentation, lineage, and governance.

• Contribute to cloud infrastructure, DevOps, data architecture, and platform engineering initiatives that enable scalable and maintainable solutions.

• Build and support machine-learning data pipelines for enterprise-grade software and data use cases.

• Help improve AI readiness through secure data exposure, semantic modeling, governed access, vector-based capabilities, and AI-enabled workflows.

• Share knowledge, coach teammates, and influence engineering practices as AI-first ways of working evolve across the organization.

• Take ownership beyond development by supporting the ongoing operation and reliability of production services, including participation in enterprise on-call and incident response processes.

Requirements

• Strong professional experience in data engineering, including SQL, data modeling, production data processing pipelines, testing, documentation, and data integrations.

• Demonstrated ability to build high-quality data products with clear ownership, definitions, testing practices, lineage, governance, and operational reliability.

• Strong understanding of AI-ready semantic modeling, business metrics, business definitions, secure API-based data exposure, and self-service analytics.

• Platform or product-oriented mindset, with experience building reusable capabilities rather than one-off solutions.

• Solid understanding of cloud infrastructure, DevOps practices, data architecture, and production engineering environments.

• Demonstrable experience using AI tools such as Cursor, Claude, ChatGPT, GitHub Copilot, or similar solutions in real engineering delivery.

• Ability to clearly explain how AI has changed your development workflow, including where it adds value, where it can fail, and how you validate and improve AI-generated outputs.

• Practical experience using AI for activities such as coding, testing, debugging, documentation, technical analysis, system design, or development productivity.

• Experience helping colleagues or teams adopt AI-first development practices through coaching, knowledge sharing, and leading by example.

• Experience building machine-learning pipelines for enterprise-class software solutions.

• Strong communication, ownership, initiative, and collaboration skills, particularly suited to working within a small platform-focused team.

• Experience working with technologies such as Snowflake, dbt, Airbyte, Airflow, Python, Terraform, Kubernetes, Helm, Azure, Kafka, Debezium, GitLab, prompt engineering, vector databases, LangChain, or LangGraph is valuable.

• Experience working with regulated, privacy-sensitive, or healthcare-related data environments would be an asset.

Benefits

• Compensation designed to recognize your skills, experience, and contribution.

• Flexible hybrid and remote working options, with teleworking available to the extent permitted by the role and operational requirements.

• Recurring hybrid work allowance.

• 4 to 6 weeks of paid vacation per year.

• 5 paid personal days annually.

• Group RRSP / DPSP plan with employer contributions.

• Comprehensive group insurance coverage starting from day one.

• Annual wellness allowance.

• Access to the Lumino Health telehealth application.

• Flexible working hours.

• Opportunity to work on a modern, AI-enabled data platform with significant scope for technical ownership and innovation.

• Collaborative environment within a small platform team where initiative, knowledge sharing, and continuous improvement are encouraged.

\nHow Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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