Job Title : Data Engineer
Location : Montreal (Day 1 onboarding onsite / in office presence 3x week)
Duration- 12 months (extendable)
Job description : We provide :
- A robust career development path offering numerous opportunities for growth, learning and advancement.
- A supportive, learning-oriented environment in collaboration with development within fast-feedback agile delivery squads
- Collaborative work within cross-functional squads, following agile practices and utilizing both cloud and on-premises technology to deliver innovative solutions.
- Encouragement for every developer to contribute their unique perspective - your ideas will be valued, and you’ll receive full support in their implementation!
- Participation in an international environment with various multidisciplinary squads, working alongside customers, product experts, and SREs.
- A dynamic environment where cutting-edge technology propels us.
- State-of-the-art offices located in the City Centre designed to enhance collaboration.
Role Responsibilities
You will be responsible for :
Collaborating with cross-functional teams to understand data requirements, and design efficient, scalable, and reliable ETL processes using Python and DataBricksDeveloping and deploying ETL jobs that extract data from various sources, transforming it to meet business needs.Taking ownership of the end-to-end engineering lifecycle, including data extraction, cleansing, transformation, and loading, ensuring accuracy and consistency.Creating and manage data pipelines, ensuring proper error handling, monitoring and performance optimizationsWorking in an agile environment, participating in sprint planning, daily stand-ups, and retrospectives.Conducting code reviews, provide constructive feedback, and enforce coding standards to maintain a high quality.Developing and maintain tooling and automation scripts to streamline repetitive tasks.Implementing unit, integration, and other testing methodologies to ensure the reliability of the ETL processesUtilizing REST APIs and other integration techniques to connect various data sourcesMaintaining documentation, including data flow diagrams, technical specifications, and processes.You have :
Proficiency in Python programming , including experience in writing efficient and maintainable code.Hands-on experience with cloud services, especially DataBricks , for building and managing scalable data pipelinesProficiency in working with Snowflake or similar cloud-based data warehousing solutionsSolid understanding of ETL principles, data modelling, data warehousing concepts, and data integration best practicesFamiliarity with agile methodologies and the ability to work collaboratively in a fast-paced, dynamic environment.Experience with code versioning tools (e.G., Git)Meticulous attention to detail and a passion for problem solvingKnowledge of Linux operating systems-Familiarity with REST APIs and integration techniquesYou might also have :
Familiarity with data visualization tools and libraries (e.G., Power BI)Background in database administration or performance tuningFamiliarity with data orchestration tools, such as Apache AirflowPrevious exposure to big data technologies (e.G., Hadoop, Spark) for large data processing/ /EEO Employer
Minorities / Females / Disabled / Veterans / Gender Identity / Sexual Orientation
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