Data Platform Lead

Are you looking for a caring, collaborative, values‑driven workplace with inspiring teammates and leaders? Do you have the ambition and desire to be the best and thrive at the most impactful global insurance provider in the world? Look no further than Zurich Canada.

If you have experience with data engineering, data science, ML engineering, and data platforms, working in a Python, SQL, and Databricks‑first environment, we would love to hear from you!

Zurich Canada is currently looking for a Data Platform Lead to join our Data team and help scale machine learning and generative AI capabilities across Zurich Canada.

Reporting to the Data Platform Leader, you will collaborate closely with US and European Zurich AI teams adapting and operationalizing models developed within the larger organization to meet Canadian business needs while building out local capabilities. This role requires strong ownership, technical depth, and business partnership.

This is a unique opportunity to build your knowledge and experience for the future in a supportive environment where your voice matters. This posting is for a new vacancy.

Zurich Canada uses artificial intelligence–enabled tools to support certain aspects of the recruitment process, including the initial review and screening of applications. Artificial intelligence is not the sole basis for candidate shortlisting or selection. All hiring decisions are reviewed and made by qualified hiring professionals.

Zurich follows a hybrid work model requiring three days per week of in‑person presence, which may include time in the office or market‑facing engagements.

• Machine Learning & GenAI
  o Design, build, evaluate, and deploy machine learning models (e.g., forecasting, optimization, classification, personalization) and generative AI solutions.
  o Leverage foundation models and GenAI platforms (e.g., OpenAI, Amazon Bedrock, Azure equivalents) where appropriate, alongside traditional ML approaches.
  o Adapt, extend, and product ionize models developed by Zurich Group AI teams for local Canadian use cases.
  o Support the full ML lifecycle: data preparation, feature engineering, training, validation, deployment, and monitoring.
  o Ensure models meet performance, scalability, and reliability expectations in production.
• Data Platform & Engineering Collaboration
  o Work closely with Data Engineering to design and optimize ML‑ready datasets and feature pipelines on Databricks.
  o Contribute to the ingestion and processing of large‑scale structured and unstructured data using Python and SQL.
  o Support data architecture evolution to enable efficient ML and GenAI workloads.
  o Apply strong data modeling and analytics engineering practices to support downstream ML use cases.
• Business Partnership & Ownership
  o Proactively identify and propose high‑value ML and GenAI use cases relevant to Zurich Canada.
  o Partner with business, product, and engineering stakeholders to translate problems into effective technical solutions.
  o Take end‑to‑end ownership of initiatives—from discovery and experimentation through production deployment.
  o Serve as a trusted thought partner to stakeholders on how ML and GenAI can drive business outcomes.
• Experimentation & Continuous Improvement
  o Design and analyze experiments (e.g., A/B testing) to validate models and inform decisions.
  o Drive continuous improvement of ML workflows through automation, standardization, and innovation.
  o Champion best practices in applied ML, GenAI, and responsible AI within the data engineering organization.

Required:

• 6+ years of experience in data science, applied machine learning, or AI product development.
• Proven track record of shipping ML models into production.
• Strong proficiency in Python and SQL.
• Hands‑on experience working in Databricks for data processing and ML workloads.
• Experience across traditional ML and generative AI use cases.
• Strong understanding of feature engineering, model evaluation, and ML lifecycle management.
• Ability to work effectively in a platform‑centric, engineering‑led environment.
• Excellent communication skills and strong stakeholder partnership abilities.
• Self‑star…