Principal Data Architect

This is a fully remote position, open to applicants in Canada.

📋 Description

• Design and architect machine learning systems capable of processing millions of real-time data points, utilizing feature stores, real-time inference pipelines, and scalable model serving frameworks to ensure optimal performance and minimal latency.

• Lead architectural decision-making for data and machine learning systems through RFC processes, guaranteeing that solutions are scalable, statistically robust, and prepared for future advancements.

• Actively contribute to data and machine learning challenges by constructing data architectures and high-performance feature engineering pipelines.

• Work closely with DevOps teams to optimize ML infrastructure (Kubernetes, cloud platforms, GPU clusters) for both training and inference workloads.

• Define and develop scalable data architectures that facilitate advanced analytics, predictive modeling, and business expansion.

• Mentor and guide Senior Data Scientists and ML Engineers, promoting strong practices in statistical rigor, MLOps, and systems thinking.

• Assist with other tasks or projects as assigned to fulfill team and business requirements.

⛳️ Requirements

• A degree in a STEM field such as Computer Science, Engineering, or Applied Mathematics, or equivalent practical experience.

• Over 5 years of cumulative experience in Data Engineering, Data Architecture, and Data Science.

• Demonstrated experience in designing and deploying large-scale, distributed data systems that manage high transaction volumes.

• Strong knowledge of cloud environments such as AWS, GCP, or Azure, along with modern data platforms like Snowflake, Databricks, or BigQuery.

• Comprehensive understanding of data modeling principles, including relational, dimensional, and NoSQL methodologies.

• Experience in building and orchestrating data pipelines using tools such as Airflow, dbt, Spark, or Kafka.

• Familiarity with data governance, security, and compliance best practices.

• Advanced proficiency in Python and SQL, with experience in data science libraries including pandas, NumPy, and scikit-learn.

• Proven success in building, training, and deploying machine learning models to address real-world business challenges.

• Experience in applying MLOps principles to transition models from experimentation to production-ready systems.

• Background in developing billing and rating systems for AI-driven or consumption-based models will be considered a plus.

• Hands-on experience in integrating AI services or creating advanced AI solutions such as RAG pipelines or API-based AI workflows will be regarded as advantageous.

🏝️ Benefits

• Work from anywhere - this is a remote position primarily targeting candidates located in the EU due to team needs and coverage considerations.

• A competitive salary that recognizes your unique skills and contributions.

• Opportunities for career advancement and professional development to help you achieve your full potential.

• Flexible work arrangements to support a healthy work/life balance.