The Position
We are looking for an experienced and hands-on Senior Integrations Developer / AI Data Integration Engineer to help lead the evolution of our modern data integration platform. This role combines traditional ETL and data engineering expertise with emerging AI-assisted integration development practices.

You will work on building scalable data ingestion and transformation pipelines while contributing to the development of a next-generation AI-assisted ETL framework that uses agents, metadata, reusable skills, and workflow orchestration to automate portions of the integration lifecycle.

The ideal candidate is equally comfortable reverse‑engineering complex client systems, designing robust transformation logic, working directly with data models and business rules, and leveraging AI development tools to accelerate delivery.

This is a foundational role within our growing integrations function and will play a critical role in shaping future integration standards, tooling, and architecture across the organization.

Key Responsibilities

Design, build, and maintain scalable ETL/ELT pipelines for onboarding external client data into the ENGIN analytics platform

Analyze 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 the design and implementation of AI‑assisted and metadata‑driven integration development frameworks

Work with agentic workflows, reusable AI skills, metadata models, and automation pipelines to accelerate integration development

Develop integration logic using Python, PySpark, SQL, and cloud‑native data processing frameworks

Support deployment and orchestration of ETL workloads within AWS‑based infrastructure environments.

Implement data quality, validation, monitoring, reconciliation, and error‑handling processes across integration workflows

Collaborate with product, delivery, customer,



and engineering teams to define data contracts, transformation requirements, and integration standards

Document integration logic, business rules, workflows, and architectural decisions

Participate in architectural planning and contribute to long‑term modernization of the company’s integration ecosystem

Assist with project estimation, implementation planning, technical discovery, and stakeholder communication

Work Location
We are a hybrid company with offices in Calgary and Toronto. We spend much of our time working remotely but also meet regularly in our offices. Only candidates that can regularly work in either of these locations will be considered.

Skills & Qualifications

5+ years of experience in ETL development, data integration, data engineering, or related roles

Strong hands‑on experience with Python and SQL for data transformation and pipeline development

Experience working with modern cloud‑based data processing and orchestration environments

Strong understanding of relational data modeling, dimensional modeling, CDC concepts, ODS/data marts, and data warehousing principles

Experience developing transformation rules, reconciliation logic, mapping logic, and data validation frameworks

Strong understanding of data profiling, pattern recognition, natural keys vs surrogate keys, and reference/lookup data management

Experience working with APIs, flat files, databases, and event‑driven integration patterns

Comfortable using AI‑assisted development tools to generate, review, and refine technical artifacts and code

Understanding of modern AI terminology and concepts such as agents, agentic workflows, metadata‑driven processing, reusable skills,



hooks, and orchestration patterns

Familiarity with AWS cloud services and distributed data processing concepts

Strong analytical, troubleshooting, and system discovery skills

Excellent communication, documentation, and stakeholder collaboration abilities

Ability to work independently in a fast‑paced and evolving technical environment

Nice to Have

Experience with PySpark, Apache Spark, EMR, Databricks, or distributed processing frameworks

Experience with orchestration and workflow tools

Experience with event‑driven architectures and messaging platforms

Familiarity with DevOps and CI/CD practices for data pipelines

Exposure to AI/LLM‑assisted software development workflows

Experience mentoring developers or helping establish technical standards and best practices

Experience working within utility, critical infrastructure, or industrial analytics environments

What Success Looks Like

Successfully onboard and modernize complex client data integrations

Help establish repeatable, scalable integration development standards

Contribute to the evolution of AI‑assisted ETL development capabilities

Improve integration delivery speed, quality, observability, and maintainabilityAct as a trusted technical contributor across integration, analytics, and platform initiatives

What We Offer

Opportunity to work on advanced AI‑assisted integration and analytics platforms

Direct impact on the architecture and future direction of the company’s data platform

High level of ownership, autonomy, and technical influence

Competitive compensation and benefits

Collaborative and technically strong engineering culture

Flexible schedule - work around a core schedule (10:00 AM - 3:00 PM) while maintaining a work‑life balance that suits you

Autonomy & Growth - take ownership of diverse responsibilities, explore cross-disciplinary opportunities, and advance your career in a dynamic, fast‑growing company

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📌 Senior Integrations Developer / AI Data Integration Engineer (Ontario)
🏢 Engineered Intelligence
📍 Ontario