Data Engineer

6 days ago

Montreal, Quebec, Canada Gala Solutions Inc Full time $80,000 - $120,000 per year

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 DataBricks-Developing 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 optimizations-Working 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 processes-Utilizing REST APIs and other integration techniques to connect various data sources-Maintaining documentation, including data flow diagrams, technical specifications, and processes.

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 pipelines-Proficiency in working with Snowflake or similar cloud-based data warehousing solutions-Solid understanding of ETL principles, data modelling, data warehousing concepts, and data integration best practices-Familiarity 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 solving-Knowledge of Linux operating systems-Familiarity with REST APIs and integration techniques

You might also have:-Familiarity with data visualization tools and libraries (e.g., Power BI)-Background in database administration or performance tuning-Familiarity with data orchestration tools, such as Apache Airflow-Previous exposure to big data technologies (e.g., Hadoop, Spark) for large data processing

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