Data & AI Engineer

Are you a data engineering visionary who thrives on tackling complex data challenges at a massive scale? Do you dream of building a global data ecosystem that empowers not only business decisions but also fuels cutting-edge machine learning initiatives? MTY, a global leader in the food industry, is seeking a Lead Data Engineer with a strong ML Engineering focus to spearhead the creation of our unified data platform. This is your chance to architect, build, and optimize the pipelines that will not only fuel our data-driven future but also enable us to leverage the power of AI and ML. Join us and make a lasting impact on how MTY harnesses the full potential of its data.

Benefits:

• 3 weeks of vacation;
• 5 days of flexible leave;
• $2000 reimbursement for professional order costs and continuing education requirements;
• Flexible working hours;
• Half-day available every Friday year-round;
• Company health and dental plans, with an additional $300 personal wellness expense account;
• Employee assistance program with access to a wide range of services from mental health to legal and financial counseling;
• Employee profit-sharing plan with employer contribution;
• Monthly company-wide recognition awards with quarterly and annual winners;
• Company social events, including but not limited to webinars, quarterly town halls, and fun activities for all;
• Casual dress code;
• Free parking at the office.

Responsibilities:

• Data Pipeline Architecture: Design and implement scalable, reliable, and efficient data pipelines that ingest, transform, and deliver data from diverse sources into our unified data platform, catering to both traditional analytics and machine learning use cases.
• Data Processing Optimization: Utilize cutting-edge technologies like Databricks, Spark, and other big data tools to optimize data processing workflows for speed, accuracy, and cost-effectiveness, with a focus on preparing data for ML model training and inference.
• Feature Engineering: Collaborate with data scientists to design and implement feature engineering pipelines that extract meaningful insights from raw data, enabling the development of high-performing machine learning models.
• ML Model Deployment: Partner with ML engineers to operationalize machine learning models, ensuring seamless integration into production environments and real-time data pipelines.
• Technology Evaluation & Adoption: Stay abreast of emerging data engineering and ML engineering technologies, advocating for the adoption of tools and platforms that support MTY's AI/ML initiatives.
• Team Leadership & Mentorship: Lead and mentor a team of data engineers, fostering a culture of collaboration, innovation, and continuous learning across both data engineering and ML engineering disciplines.
• Cross-Functional Collaboration: Partner with data scientists, analysts, and business stakeholders to understand data and ML requirements and deliver solutions that drive business value.
• Performance Monitoring & Tuning: Continuously monitor pipeline performance, identify bottlenecks, and implement optimizations to ensure optimal throughput and responsiveness for both analytics and ML workloads.

Qualifications:

• Proven Experience: 5+ years of hands-on experience in data engineering, with a demonstrated track record of building and managing complex data pipelines in cloud environments (Azure, GCP), including experience with ML data pipelines.
• Technical Expertise: Deep understanding of data processing frameworks (Spark, Databricks), ETL/ELT processes, data warehousing concepts, data modeling best practices, and machine learning pipelines.
• Programming Skills: Proficiency in Python, Scala, or other relevant programming languages for data manipulation, transformation, and ML model development.
• Cloud Technologies: Experience with cloud-based data platforms (Azure Data Lake Storage Gen2, Google Cloud Storage) and data processing services (Azure Databricks, GCP Dataproc), as well as cloud-based ML platforms (Azure Machine Learning, Google AI Platform).
• ML Engineering Skills: Familiarity with ML frameworks (TensorFlow, PyTorch), model deployment strategies, and MLOps practices.
• Leadership & Communication: Strong leadership skills with the ability to motivate and mentor a team, coupled with excellent communication skills to collaborate effectively with diverse stakeholders, including data scientists and ML engineers.
• Problem-Solving Aptitude: A passion for solving complex data challenges and a proactive approach to identifying and resolving issues, both in data engineering and ML engineering contexts.
• Agile Mindset: Experience working in Agile environments and embracing iterative development approaches.

Please note that any offer of employment will be conditional upon a background check, including a criminal record check.

The majority of our clients and a large proportion of our employees are outside Quebec