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fgf brands

Senior Data Engineer

Toronto, ON, Canada
Greater Toronto Area, ON, Canada

Apply by: Sep 21, 2027
Experience: 5+ years of experience in Data Engineering, with at least 3 years architecting on Azure Databricks.
Posting language: English
Posted: Sep 21, 2026

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Original job description

Job Description

Senior Data Engineer

We’re a naan traditional company…

Summary

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 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.

Reporting to the Data Architect, the Senior Data Engineer will be responsible for the following duties, and complete special initiatives and projects, as assigned.

What FGF Offers:

FGF believes in Home Grown Talent, accelerated career growth with leadership training. Unleashing Your Potential
Competitive Compensation, Health Benefits, & a generous flexible medical / Health spending account
RRSP matching program
Tuition reimbursement
Discount program that covers almost everything under the sun - Restaurants, gyms, shopping etc.

Primary 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.

Required Experience

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.

What is the recipe for a great career at FGF?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.

Disclaimer: The above describes the general responsibilities, required knowledge and skills. Please keep in mind that other duties may be added or this description may be amended at any time.

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.

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More about this job

Responsibilities

The Senior Data Engineer will architect and deliver scalable real-time and batch data pipelines using Azure Databricks and Lakehouse architecture. They will also lead data modeling efforts, implement CI/CD workflows, and mentor junior engineers to ensure high-performing data solutions.

Requirements

Candidates must have at least 5 years of data engineering experience, including 3 years specifically with Azure Databricks. Proficiency in Python, SQL, Delta Lake, and CI/CD practices is required to succeed in this role.

Skills

Azure Databricks
Spark
Delta Lake
Python
SQL
Lakehouse architecture
Data modeling
CI/CD
Azure DevOps
ETL/ELT
Data orchestration
Distributed computing
Data engineering
Cloud platforms
Data quality
Observability

Benefits

Competitive compensation
Health benefits
Flexible medical/health spending account
RRSP matching program
Tuition reimbursement
Discount program

Visa sponsorship

Not detected in the job text

Keywords

Data Engineering
Azure Databricks
Spark
Delta Lake
Lakehouse
Python
SQL
ETL
ELT
CI/CD
Azure DevOps
Data Modeling
Data Warehouse
Azure Data Factory
Databricks Workflows
Git
Distributed Computing
RESTful APIs
Kafka
Azure Event Hubs
Spark Structured Streaming
NoSQL
MongoDB
MLOps
Power BI
Tableau
Data Governance
Data Lineage
Cloud Platforms
Semantic Modelling

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