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Entry Level Databricks Data Engineer Jobs in Montreal, QC

About You We're hiring a Senior Data Engineer for Data Insights in Montreal-someone with a Data as ... Databricks: Hands-on Databricks experience (workspaces, jobs/workflows, Spark SQL/PySpark, Delta ...

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Senior Data Engineer A propos d'AppDirecte Devenez un citoyen du monde a l'ere numerique et ... Databricks : Experience pratique avec Databricks (espaces de travail, taches/workflows, Spark SQL ...

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Master's degree or PhD in Computer Science, Statistics, Mathematics, Engineering, Operations ... Familiarity with Databricks, PySpark, MLflow, experimentation tooling, and cloud-native deployment ...

Document data engineering processes, data flows, and system configurations to facilitate knowledge ... Hands-on experience with Apache Spark and Databricks for big data processing and transformation.

Senior Data Scientist Montréal, Canada The Sr. Data Scientist will conduct detailed analysis of ... Excellent programming skills using notebook environments, e.g. Jupyter, Databricks, and familiarity ...

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Entry Level Databricks Data Engineer information

What is an Entry Level Databricks Data Engineer?

An Entry Level Databricks Data Engineer is a professional who uses Databricks, a cloud-based data analytics platform, to design, build, and maintain data pipelines. They are responsible for preparing and processing large datasets, ensuring data quality, and enabling analytics and machine learning workflows. Typically, they work with tools such as Apache Spark, SQL, and Python, and collaborate with data analysts and data scientists to deliver data-driven solutions. As entry-level engineers, they are expected to have foundational knowledge of data engineering concepts and be eager to learn more advanced techniques on the job.

What are the key skills and qualifications needed to thrive as an Entry Level Databricks Data Engineer, and why are they important?

To thrive as an Entry Level Databricks Data Engineer, you need a foundational understanding of data engineering concepts, SQL, and Python or Scala, typically supported by a relevant degree in computer science or a related field. Familiarity with Databricks, Apache Spark, cloud platforms (like AWS or Azure), and optional certifications such as Databricks Data Engineer Associate are highly valuable. Strong analytical thinking, attention to detail, and effective communication skills help you collaborate with teams and solve complex data challenges. These skills and qualities are essential for building reliable data pipelines, ensuring data quality, and delivering actionable insights in a fast-paced environment.

What are some common challenges faced by entry-level Databricks Data Engineers, and how can they effectively overcome them?

Entry-level Databricks Data Engineers often face challenges such as learning to optimize Apache Spark jobs, managing complex data pipelines, and understanding cloud-based workflows. To overcome these, it's important to dedicate time to hands-on practice with Databricks notebooks, collaborate closely with more experienced engineers, and actively participate in code reviews and team discussions. Leveraging Databricks' extensive documentation and community forums can also help troubleshoot issues and stay updated on best practices.
What are the most commonly searched types of Databricks Data Engineer jobs in Montreal, QC? The most popular types of Databricks Data Engineer jobs in Montreal, QC are:
What are popular job titles related to Entry Level Databricks Data Engineer jobs in Montreal, QC? For Entry Level Databricks Data Engineer jobs in Montreal, QC, the most frequently searched job titles are:
What job categories do people searching Entry Level Databricks Data Engineer jobs in Montreal, QC look for? The top searched job categories for Entry Level Databricks Data Engineer jobs in Montreal, QC are:
Infographic showing various Entry Level Databricks Data Engineer job openings in Montreal, QC as of July 2026, with employment types broken down into 1% As Needed, 85% Full Time, 10% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution.

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Job description

Pour la version francaise de cette description de poste, veuillez consulter le lien suivant / For the French version of this job description, please refer to the following link:

  • Ingenieur(e) de donnees senior

About AppDirect

Become a digital, global citizen and enable the new generation of digital entrepreneurs around the world.  AppDirect offers a subscription commerce platform to sell any product, through any channel, on any device - as a service.  We power millions of subscriptions worldwide for organizations.  We do this by our values-driven culture-one that enables you to Be Seen, Be Yourself, and Do Your Best Work.

About the Data Insights Team

Our mission is to unify data from every business unit into a governed lakehouse and semantic layer, powering analytics, AI, reports, data sharing, and both internal and customer-facing dashboards.

About You

We're hiring a Senior Data Engineer for Data Insights in Montreal-someone with a Data as a Product mindset who builds production pipelines and models others can trust and reuse.

You'll build production data products and lakehouse pipelines that power analytics and both internal and customer-facing dashboards-partnering across engineering and product, establishing clear data contracts, and leaving patterns others can reuse.

What You'll Do and How You'll Make an Impact

  • Platform Architecture & Modeling: Design, build, and evolve the lakehouse data platform-reusable models and pipelines on Snowflake + dbt, with Databricks workloads where they fit-so analytics and product teams get reliable, governed data products.
  • Requirements & Stakeholder Partnership: Translate product and business requirements into data models and pipelines-working with PMs, BUs, and engineers so domain logic lands correctly in production.
  • Pipeline Modernization: Migrate legacy ETL processes to modern, efficient streaming and incremental pipelines, choosing Snowflake or Databricks based on fit.
  • Snowflake Performance & Cost: Operate and tune Snowflake for reliability and efficiency-warehouse sizing and utilization, clustering/partitioning where it pays off, and visibility into credit spend so scale doesn't mean runaway cost.
  • AI-Assisted Operations: Apply AI-assisted development tools and spec-driven workflows to design, automate, and ship data pipelines and platform.
  • Self-Service Enablement: Facilitate scoped data onboarding and empower business unit engineers to build their own data products on top of our platform.
  • Customer-Facing Data Products: Build and evolve data behind customer-facing products-including the reporting service and App Insights-so pipelines and models deliver trustworthy product experiences.
  • Data Quality & Trust: Ensure data quality by driving and implementing robust data governance, automated testing, validation techniques, and lineage.
  • Metadata Management: Curate rich metadata in Unity Catalog and Snowflake to power downstream consumption, including AI agents and our semantic layer (Cube.dev).
  • Research & Innovation: Research solutions to complex problems and lead proof-of-concepts to evaluate emerging technologies.
  • Documentation & Culture: Author and maintain high-quality documentation to support knowledge sharing and AI-assisted workflows.

What we're looking for

  • AI-Assisted Development: Strong understanding of AI-assisted development workflows, with proven hands-on experience using tools such as Cursor, Claude, OpenCode, GitHub Copilot, or ChatGPT to improve efficiency, automation, and code quality.
  • Spec-Driven Development: Experience with spec-driven development: turning requirements into clear specs/plans and acceptance criteria, then implementing them (including AI-agent-assisted workflows).
  • Snowflake Expertise (core skillset): 2+ years building and operating production data pipelines and models on Snowflake using SQL, Python, and dbt-shipping reliable ELT/transformations, owning quality and performance in production.
  • dbt Mastery: 2+ years of hands-on experience building modular, version-controlled, and tested data models using dbt (data build tool), treating transformation as software engineering (Git workflows, code review, automated tests).
  • AWS: 2+ years of experience with AWS cloud services.
  • Data Governance: A solid understanding of data quality, lineage, validation techniques, and data governance.
  • Collaboration & Communication: Ability to communicate complex technical concepts effectively to both technical and non-technical stakeholders, gather requirements, and work effectively in a distributed team.

Preferred / Additional Strengths

  • Databricks: Hands-on Databricks experience (workspaces, jobs/workflows, Spark SQL/PySpark, Delta Lake) to contribute to lakehouse work alongside Snowflake.
  • Managed Ingestion (Fivetran): Exposure to Fivetran (or similar ELT connectors) for reliable source-to-warehouse ingestion, connector governance, and schema-evolution handling.
  • Semantic Layer (Cube.dev): Exposure to Cube.dev (or a similar semantic/metrics layer) for governed, self-serve analytics and consistent metrics across products and consumers.
  • Real-Time Streaming: Strong preferred experience building and maintaining real-time data solutions using streaming platforms like Apache Kafka.

At AppDirect, we believe that innovation thrives in an environment that houses diversity of excellence, experience and thought. We respect each AppDirector as their own fingerprint; unique with no one alike. We foster an environment of inclusion without regard to race, religion, age, sexual orientation, or gender identity enabling AppDirectors to embrace their uniqueness to do their best work. As such, we strongly encourage applications from Indigenous peoples, racialized people, people with disabilities, people from gender and sexually diverse communities, and/or people with intersectional identities.

At AppDirect we take privacy very seriously. For more information about our use and handling of personal data from job applicants, please read our Candidate Privacy Policy. For more information of our general privacy practices, please see AppDirect Privacy Notice: 

https://www.appdirect.com/about/privacy-notice

At AppDirect, AI tools may assist our recruitment team with administrative automations - always under human oversight. AI tools do not make hiring decisions or solely automated decisions about your candidacy - all decisions are made by our people. By submitting your application, you acknowledge that your information may be processed in this way. You may request access or deletion at any time by contacting privacy@appdirect.com.

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