Data Engineer – Data Platform (AI-Enabled) in Canada Creek, Nova Scotia at Jobgether

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.

• 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.

• 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.

• 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.