At a Glance
- Tasks: Design and deliver scalable data pipelines using Azure Databricks and modern data platforms.
- Company: FGF Brands, a dynamic company with an entrepreneurial spirit.
- Benefits: Competitive pay, health benefits, tuition reimbursement, and flexible spending accounts.
- Other info: Great career growth opportunities and a supportive team culture.
- Why this job: Join a fast-paced environment where your creativity drives innovation in data engineering.
- Qualifications: 5+ years in Data Engineering with expertise in Azure Databricks and Python.
The predicted salary is between 121500 - 148500 $ per year.
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.
Reporting to the Data Architect, the Senior Data Engineer will be responsible for the following duties:
- 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.
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.
Senior Data Engineer in Winnipeg employer: FGF Brands
Cerebro Technologies is an exceptional employer that fosters a dynamic and innovative work culture, perfect for those looking to make a significant impact in the tech industry. With a strong focus on employee growth through leadership training and a commitment to leveraging cutting-edge AI technologies, team members are empowered to unleash their potential while enjoying competitive compensation and comprehensive benefits. Located in a fast-paced startup environment, employees thrive on collaboration and creativity, driving the future of manufacturing operations with meaningful contributions.