The mandate

You will join an established analytics delivery team to design, develop and evolve data pipelines on Azure Databricks, in a modern and demanding cloud environment. This is not a heads-down development role. You will work daily with analysts, architects, a technical lead and business stakeholders. Your ability to listen, explain and build trust matters as much as your technical depth, if not more.

Responsibilities

Design, develop and optimize data ingestion and transformation pipelines on Azure Databricks (SQL, Python, Spark) Orchestrate workloads via Azure Data Factory and Databricks workflows Apply and evolve data models (medallion architecture, star and snowflake schemas, wide tables, Data Vault) Deliver iterative development, testing and deployment of features in an Agile/DevOps setting Write and maintain unit and QA tests Monitor daily processing and correct anomalies Evolve existing analytics solutions with improvements, automation and optimizations Write and maintain technical documentation for understanding, operation and maintenance of solutions Document work in Jira and Confluence Support users and maintain links with stakeholders Perform functional analysis tasks as needed (clarifying needs, translating into technical requirements)

Requirements

Bachelor's degree in computer science, software engineering or a related field, or equivalent combination of education and experience Minimum 6 to 7 years of Databricks experience (no junior profiles) Databricks Certified Data Engineer Associate required Databricks Certified Data Engineer Professional (strong asset) Fluent French, spoken and written — the mandate runs primarily in French Functional English (level 3 of 5) — ability to read technical documentation and interact with English-speaking stakeholders as needed Available to work primarily onsite in downtown Montreal

Technical skills

Strong knowledge of the Azure Databricks platform and its capabilities Strong knowledge of Azure Data Factory for orchestration Strong knowledge of SQL and Python applied to data transformation Solid knowledge of distributed processing concepts, Spark and Big Data Solid knowledge of ETL concepts, medallion architecture, and data ingestion and exposure processes Solid knowledge of data modeling and data products Solid knowledge of Git in Azure DevOps for source control and branching Solid knowledge of Python libraries and building new ones for reusability Solid knowledge of agentic AI and classical AI fundamentals, MLOps tooling and the AI solution lifecycle Knowledge of Agile process within a DevOps team, plus Jira and Confluence Demonstrated ability to use generative AI in daily work Power BI knowledge (asset) Behavioural skills (essential) Communication — able to clearly explain technical concepts to business stakeholders, verbally and in writing Adaptability — comfortable in an environment that shifts and where priorities get clarified along the way Teamwork — active contributor to a delivery team, open to feedback, willing to help Openness and consideration — collaborative posture with colleagues and stakeholders Agility and results orientation — sense of priorities and focus on delivery Commitment to growth — technical curiosity and willingness to advance team practices Technical leadership in their area of expertise, ability to influence without formal authority What we offer A 16-month mandate with a major Quebec client A leading-edge technology environment (Azure Databricks, AI, MLOps) A collaborative team where relationship quality counts as much as code quality Competitive terms based on experience