The Data Engineer will advance data-driven decision-making by designing and implementing scalable data solutions, building modern data pipelines, and enabling analytics, reporting, machine learning, and generative AI use cases. The role will collaborate with business stakeholders and technical teams to translate requirements into reliable, user-friendly, enterprise data solutions.

Responsibilities:

- Collaborate with colleagues and business partners to provide tools for routine and non-routine data analysis.
- Accelerate data initiatives by leveraging AI-enabled technologies and processes.
- Translate business requirements into technical solutions using strong business acumen.
- Analyze current business practices, processes, and procedures to identify future opportunities.
- Assess business needs and create customized data design services.
- Provide exceptional support to business partners.
- Develop foundational components for evolving enterprise data solutions.
- Architect, build, and maintain modern data pipelines.
- Implement effective metrics, monitoring, alerting, and data-quality controls.
- Make independent decisions and provide technical guidance to peers.
- Create and promote technical best practices for data modeling and report design.
- Prepare, transform, and govern data for analytics,



machine learning, and generative AI use cases.
- Perform other related duties as required or assigned.

Qualifications:

- 5+ years of experience in data engineering and/or data warehousing.
- 4+ years of hands-on experience with Azure Databricks.
- Experience supporting AI-ready data solutions, including preparing, transforming, and governing data for analytics, machine learning, and generative AI use cases.
- Proficiency in Agile development methodologies, including DevOps concepts.
- Proficiency with version-control platforms such as Git.
- Mastery of T-SQL and ANSI SQL.
- Solid Python capability for data-related tasks and integration.
- Strong analytical, problem-solving, collaboration, and communication skills.
- Ability to work independently and provide guidance to peers.

Tools and Technologies:

- Azure Databricks
- Azure data platform services
- T-SQL and ANSI SQL
- Python
- Git
- DevOps tooling
- Data warehousing technologies
- ETL/ELT and data-pipeline frameworks
- AI/ML data-enablement technologies

Pay: $60.00-$70.00 per hour Expected hours: 40.0 per week

Experience

- data engineering and/or data warehousing: 10 years (required)

Work Location: Remote

📌 Data Engineer (Greater Toronto Area)
🏢 Cloud Destinations
📍 Greater Toronto Area