Data Engineer
- Canada
Full-time
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Job details
- Job type
- Full-time
- Posting language
- English
- Posted
Original job description
Project Description:
Our client is an energy solutions provider. Our AI-enabled platform supports operations, tracking and decision-making to optimize large-scale renewable and traditional energy portfolios. We're delivering a key client MVP in February 2027, and the project continues into 2028. Our stack: Ruby on Rails, Node.js/TypeScript and Python services, PostgreSQL, Snowflake and AWS. We're looking for an autonomous data engineer to strengthen our data foundation through good modeling, clean schemas, reliability and automation.
Responsibilities:
Work closely with product teams to help define and execute technical criteria
Architect and maintain robust data ingestion pipelines that feed both our application and analytics
Design well-modeled, layered tables with clean schemas that turn raw data into analytics-ready data
Help onboard client data from a variety of sources, such as Databricks via Delta Sharing, and integrate it with our existing services and workflows
Make pipelines reliable and automated: data quality tests, monitoring, safe reprocessing and schema change handling
Build a documented, well-tested data foundation that serves the app, analytics and future AI use cases
Mandatory Skills Description:
Mid-to-senior data engineer who has owned the design of production data pipelines end to end, working as an autonomous IC
Designing and building production ingestion pipelines from APIs, files and shared-data sources, using a workflow orchestrator (any tool, e.g. Airflow, Dagster or Step Functions)
Production experience with a cloud data warehouse (Snowflake preferred)
Strong SQL, plus production experience in Python (preferred) or Node.js/TypeScript
AWS or another enterprise cloud platform
AI-native development: daily use of agentic AI coding tools, and experience scaling shared AI workflows across a team and into the development lifecycle, including CI/CD
Strong English and communication skills
Nice-to-Have Skills Description:
dbt
Preparing data for AI/LLM use (e.g. semantic layers, metadata, retrieval-ready datasets)
Infrastructure as code (e.g. Terraform)
Exposure to energy, utilities or sustainability data
More about this job
Responsibilities
Design and maintain reliable, automated data ingestion pipelines that support application operations and analytics, including onboarding client data from varied sources. Build well-modeled, documented, and tested data tables and schemas, with data quality checks, monitoring, safe reprocessing, and support for schema changes.
Requirements
The role requires mid-to-senior experience independently owning production data pipelines end to end, strong SQL, production experience with Python or Node.js/TypeScript, and experience with a cloud data warehouse and enterprise cloud platform. Candidates should have experience with workflow orchestration, daily use of agentic AI coding tools and scaling AI workflows through team development and CI/CD, along with strong English and communication skills.
Skills
- Data Engineering
- Production Data Pipelines
- Data Ingestion
- SQL
- Python
- Node.js
- TypeScript
- Snowflake
- AWS
- Workflow Orchestration
- Data Modeling
- Data Quality Testing
- Pipeline Monitoring
- Schema Management
- AI-Native Development
- CI/CD
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
- Energy
- Environmental & Sustainability
Keywords
- Data Engineering
- Data Ingestion Pipelines
- Data Modeling
- SQL
- Python
- Ruby On Rails
- Node.js
- TypeScript
- PostgreSQL
- Snowflake
- AWS
- Airflow
- Dagster
- Step Functions
- Databricks
- Delta Sharing
- Data Quality
- Pipeline Monitoring
- Schema Management
- Workflow Orchestration
- Agentic AI Coding Tools
- CI/CD
- Dbt
- Semantic Layers
- Retrieval-Ready Datasets
- Terraform
- Energy Data
- Utilities Data
- Sustainability Data