Data Engineer| Level 4 (CAD) - RSR MSP

• 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.

• 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

• 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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