Full-Time Lead Data Architect
Milk Moovement is hiring a remote Full-Time Lead Data Architect. The career level for this job opening is Experienced and is accepting Toronto, Ontario based applicants remotely. Read complete job description before applying.
Milk Moovement
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About the Company
Milk Moovement is building a world-class team focused on getting the right milk to the right place at the right time. Our growing herd of employees is driven to provide our clients with the data they need to make critical decisions that impact their operations and ultimately your favourite dairy products. We are a young VC-backed company with humble roots and massive ambitions to disrupt the dairy supply chain. We think differently, act nimbly, and always leave things better than we found them. We're expanding our team to further our mission. Find us out on Twitter, Instagram, LinkedIn (@milkmoovement), and our home page to learn more or hit "apply" below!
The Role
We're hiring a Data Architect to join our team! Milk Moovement is a data analytics platform for modern dairy supply chains. Well-structured data is integral to our mission of revolutionizing the dairy supply chain. As the Data Architect, you will oversee the continued evolution of our data platform including the data warehouse, transformation pipelines, visualization tools, and supporting cloud infrastructure.
Responsibilities
- Develop and maintain data architectures to support internal and external customer analytics as well as AI/ML workloads.
- Supervise business analytics and reporting efforts internally and for external cooperative customers.
- Participate in design sessions to ensure data models for new products are scalable and extensible.
- Collaborate with the team to enable AI feature engineering, model training, and deployment at scale.
- Provide mentorship to ensure alignment with data engineer best practices.
Qualifications
- Proven track record of deploying large-scale data platforms, with specific experience in Snowflake.
- Familiarity with dbt for data transformation and Dagster (or other tools) for pipeline orchestration.
- Solid fundamentals in data warehousing concepts and transformation design patterns (real-time, batch, event-driven workflows).
- Hands-on experience building cloud native data solutions in AWS.
- Proficiency in SQL and Python.
- Experience using Terraform to build data infrastructure, deployed via CI/CD pipelines.
- Ability to collaborate, prioritize, and deliver value in a dynamic workplace.
Preferred Qualifications
- Background in MLOps and productionizing AI/ML models. Experience with implementing ML models in Snowflake is a bonus.
- Exposure to common ML Frameworks (TensorFlow, MLlib, PyTorch, or Scikit-learn)
- Experience using container-based services (Docker, ECS, Kubernetes)
- Experience building real-time transformation systems (Flink, Kafka Streams)
- Experience designing and building data pipelines that integrate and process data from document-oriented NoSQL and relational SQL databases.