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.

Check below to see if you have what is needed for this opportunity, and if so, make an application asap.

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