Senior Data Engineer

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 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 APls and other integration techniques to connect various data sources • Maintaining 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 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 • Experience with ServiceNow integration