Data Architect

Konrad•Toronto, ON

34d•$120,000 - $150,000•Hybrid

About The Position

As a Data Architect, you are a technically strong and curious problem-solver who applies expertise in data science, enterprise data architecture, system design, and data governance best practices to solve complex business challenges. You design and oversee the development of scalable, secure, and reliable data solutions, and can clearly communicate the value of your designs to both technical and business audiences. You will collaborate closely with data engineers, analysts, product managers, and clients to design and deliver data & AI solutions that drive measurable impact. You are comfortable working with large databases, designing enterprise data systems, and contributing to AI-enabled products in strict regulatory environments. As a senior contributor on the team, you bring a strong foundation in data science, system design, and modern data tooling.

Requirements

Minimum 5+ years of experience in a data science, machine learning, or solution architect roles
Strong proficiency in Python (or similar) and experience with data science libraries and frameworks
Solid foundation in statistics, probability, and machine learning techniques
Experience designing and managing the build-out of cloud-based data platforms and data warehouses (e.g., Snowflake, Databricks BigQuery, Redshift)
Familiarity with model deployment, monitoring, and lifecycle management
Experience with containerization (e.g., Docker) and building production APIs (e.g., FastAPI) and applications (e.g., Django or Flask).
Experience collaborating with data engineering teams on production-grade solutions
Strong problem-solving skills and the ability to frame ambiguous business problems into technology solutions and gaining stakeholder buy-in
Excellent communication and presentation skills
Experience working in agile, consulting, or cross-functional environments

Nice To Haves

Have you taken any courses at BrainStation? A lot of our design and development best practices and processes are taught during our courses, make sure to highlight this experience in your cover letter if you have!

Responsibilities

Partner with clients and internal teams to identify opportunities where data science and machine learning can drive business value
Explore, analyze, and prepare large datasets for modeling and experimentation
Design, build, and validate statistical, predictive, and machine learning models
Develop and deploy scalable data science and AI solutions in collaboration with engineering teams
Evaluate model performance and continuously iterate to improve accuracy (including A/B testing and causal analysis)
Lead data modernization & migration projects at large enterprises
Communicate findings, methodologies, and recommendations clearly to technical and non-technical stakeholders
Stay current with emerging data science, AI, and machine learning techniques and tools