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About the Role

We are seeking a Senior Data Engineer with deep expertise in designing and delivering scalable, real-time streaming as well as batch data pipelines and solutions using modern data platforms such as Azure Databricks. In this role, you will lead the end-to-end design, and development of scalable data solutions that power analytics, machine learning, and operational insights across the organization. This role is perfect for someone who thrives in a dynamic environment, is passionate about data engineering and architecture, and has a strong grasp of Lakehouse patterns, data modeling, and CI/CD practices. Creativity, adaptability, and a problem-solving mindset are essential as you'll drive innovation in data engineering practices to meet ever-evolving business needs.

Responsibilities

Architect, implement and deliver real-time streaming and batch data pipelines using Spark, Delta Lake, and Databricks.
Design and maintain a Lakehouse architecture supporting both structured and semi-structured data, supporting business intelligence and operational analytics use cases.
Develop data models for analytics and reporting, including dimensional modeling and data mart design.
Build and maintain CI/CD pipelines for data workflows using tools like Azure DevOps, or similar.
Collaborate with stakeholders to understand data challenges and translate requirements into high-performing technical solutions.
Implement data quality, observability, and monitoring frameworks to ensure pipeline reliability.
Lead and mentor junior engineers, promoting best practices in data engineering and software development.
Contribute to the technical strategy and long-term vision for the data platform.
Stay current with emerging technologies and trends in data engineering and cloud platforms.

Requirements

5+ years of experience in Data Engineering, with at least 3 years architecting on Azure Databricks.
Deep knowledge of Delta Lake, Medallion Architecture, and Lakehouse patterns; experience applying these to production-grade pipelines.
Expert in Python and SQL for ETL/ELT logic, data transformation, and orchestration.
Solid understanding of data warehouse modeling (e.g., star/snowflake schemas) and translating business requirements into scalable data models.
Experience with data orchestration tools e.g. Azure Data Factory, Databricks Workflows, etc.
Strong Experience deploying and monitoring jobs in production using Databricks Jobs and CI/CD workflows.
Strong knowledge of CI/CD practices, version control (Git), Databricks CLI, Unit Testing, etc.
Familiarity with distributed computing concepts and performance optimization in Spark (DataFrames, Spark SQL, RDD, etc.).
Experience with RESTful APIs, microservices, and data integration patterns.
Familiarity with streaming and event-driven architectures (e.g., Kafka, Azure Event Hubs); hands-on experience with Spark Structured Streaming is an asset.
Exposure to NoSQL databases (e.g., MongoDB) and real-time ingestion patterns is a plus.
Ability to translate ambiguous requirements into scalable, production-ready systems.
Excellent communication, documentation, and stakeholder management skills.
Strong analytical and problem-solving abilities; comfort working in fast-paced environments.
Exposure to AI agents, machine learning pipelines, and MLOps practices considered an asset.
Continuous learning mindset; stays current with advancements in the Azure Databricks ecosystem.
Familiarity with BI tools such as Power BI or Tableau, data cataloging, logging and observability tools and semantic modelling is a plus.
Knowledge of data governance, lineage, and security best practices in cloud environments.

Skills

Azure Databricks
Spark
Delta Lake
Lakehouse architecture
Data modeling
CI/CD
Azure DevOps
Python
SQL
ETL/ELT
Data warehouse modeling
Azure Data Factory
Databricks Workflows
Git
Databricks CLI
Unit Testing
Spark Structured Streaming
RESTful APIs
Microservices
NoSQL databases
MongoDB
Power BI
Tableau
Data cataloging
Logging
Observability tools
Semantic modelling
Data governance
Data lineage
Data security

Location

Ontario

Work Type

Full-time

Experience Level

Senior
5+ years of experience in Data Engineering
3 years architecting on Azure Databricks

Benefits

Competitive Compensation
Health Benefits
Generous flexible medical / Health spending account
RRSP matching program
Tuition reimbursement
Discount program

About the Company

We’re a naan traditional company…
Working at FGF Brands, there is never a dull moment! As a successful company that is continually growing there is always challenging yet rewarding work to be a part of. We have an entrepreneurial spirit which encourages all our team members to use their own creativity and out of the box thinking to come up with solutions and new ideas.

Equal Opportunity

In compliance with Ontario’s Bill 190, we confirm that this posting represents a current, existing vacancy within our organization.
FGF Brands may use Artificial Intelligence (AI) tools as part of our recruitment and selection process. These tools may assist in screening, assessing, or selecting applicants. AI tools are used to support our recruitment process, with final hiring decisions made by our recruitment and hiring teams.
FGF Brands is committed to providing an accessible recruitment process. Accommodations are available upon request for candidates taking part in all aspects of the recruitment and selection process. If you require an accommodation, please let our recruitment team know, and we will work with you to meet your accessibility needs.