Job Description

Senior Data Engineer

We’re a naan traditional company…

Summary

We are seeking aSenior 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 asAzure 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 ofLakehouse 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 versatile 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, implementand deliver real-time streaming and batch data pipelinesusing Spark, Delta Lake, and Databricks.
- Design and maintain aLakehouse architecturesupporting both structured and semi-structured data,



supporting business intelligence and operational analytics use cases.
- Developdata modelsfor analytics and reporting, including dimensional modeling and data mart design.
- Build and maintainCI/CD pipelinesfor data workflows using tools like Azure DevOps, or similar.
- Collaborate with stakeholders to understand data challenges and translate requirements into high-performing technical solutions.
- Implementdata quality, observability, and monitoringframeworks to ensure pipeline reliability.
- Lead and mentor junior engineers, promoting best practices in data engineering and software development.
- Contribute to thetechnical strategy and long-term visionfor 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 onAzure Databricks.
- Deep knowledge of Delta Lake, Medallion Architecture, and Lakehouse patterns; experience applying these to production-grade pipelines.
- Expert inPythonandSQLfor ETL/ELT logic, data transformation, and orchestration.
- Solid understanding ofdata warehouse modeling(e.g., star/snowflake schemas) and translating business requirements into scalable data models.
- Experience withdata orchestration toolse.g.



Azure Data Factory, Databricks Workflows, etc.
- Strong Experience deploying and monitoring jobs in production using Databricks Jobs and CI/CD workflows. Strong knowledge ofCI/CD practices, version control (Git), Databricks CLI, Unit Testing, etc.
- Familiarity withdistributed computing conceptsand performance optimization in Spark (DataFrames, Spark SQL, RDD, etc.).
- Experience withRESTful 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 withBI toolssuch 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 re

📌 Senior Data Engineer (Canada)
🏢 fgf brands
📍 Canada