Senior Integrations Developer / AI Data Integration Engineer

About the role

Engineered Intelligence Inc., a power infrastructure technology company, is looking for an experienced Senior Integrations Developer / AI Data Integration Engineer to lead the evolution of its modern data integration platform. The role combines traditional ETL and data engineering with emerging AI-assisted integration practices, building scalable ingestion and transformation pipelines and contributing to an AI-assisted ETL framework based on agents, metadata, reusable skills and workflow orchestration. It is a foundational role in the growing integrations function.

Key responsibilities

• Design, build and maintain scalable ETL/ELT pipelines for onboarding external client data into the ENGIN analytics platform
• Analyse and reverse-engineer client systems, source data structures and business processes to define integration approaches
• Develop transformation logic, mapping rules, reconciliation processes and validation workflows for complex utility and enterprise datasets
• Contribute to AI-assisted and metadata-driven integration frameworks, including agentic workflows, reusable AI skills and automation pipelines
• Build integration logic in Python, PySpark, SQL and cloud-native data processing frameworks
• Support deployment and orchestration of ETL workloads in AWS-based environments
• Implement data quality, validation, monitoring, reconciliation and error-handling processes
• Collaborate with product, delivery, customer and engineering teams on data contracts, transformation requirements and integration standards
• Document integration logic, business rules, workflows and architectural decisions, and assist with estimation, planning, technical discovery and stakeholder communication

Required profile

• 5+ years of experience in ETL development, data integration, data engineering or related roles
• Hybrid work: regular presence in either Calgary or Toronto office required
• Nice to have: experience mentoring developers, establishing technical standards, and working in utility, critical infrastructure or industrial analytics environments

Required skills

• Python and SQL for data transformation and pipeline development
• Relational and dimensional data modelling, CDC, ODS/data marts and data warehousing
• APIs, flat files, databases and event-driven integration patterns
• AI-assisted development tools and concepts such as agents, agentic workflows, metadata-driven processing and reusable skills
• AWS cloud services and distributed data processing
• Nice to have: PySpark, Spark, EMR, Databricks, workflow orchestration tools, event-driven messaging, DevOps and CI/CD for data pipelines

What we offer

• Work on advanced AI-assisted integration and analytics platforms with direct impact on the data platform's architecture
• Competitive compensation and benefits
• Flexible hours around a core schedule of 10:00 AM - 3:00 PM
• Autonomy, ownership and a collaborative, technically strong engineering culture