Description

You will build and maintain scalable data pipelines.

You will own the end-to-end engineering lifecycle: extraction, cleansing, transformation, and loading.

Responsibilities

• Design and develop efficient ETL processes using Python and DataBricks.
• Create and manage data pipelines, implementing error handling and performance optimizations.
• Conduct code reviews and enforce coding standards to maintain code quality.
• Develop tooling and automation scripts to streamline repetitive data tasks.

Required Skills

• 10+ years of professional experience in data engineering.
• Proficiency in Python, writing efficient and maintainable code.
• Hands-on experience with cloud services, specifically DataBricks.
• Proficiency with Snowflake or similar cloud data warehousing solutions.
• Solid understanding of ETL principles, data modelling, and data integration best practices.
• Experience with code versioning tools, including Git.
• Familiarity with REST APIs and integration techniques.
• Knowledge of Linux operating systems.
• Experience working in an agile development environment.

Preferred Skills

• Familiarity with Apache Airflow for data orchestration.
• Exposure to Big Data technologies like Spark or Hadoop.
• Experience with data visualization tools such as Power BI.

Key Skills

Education

Any Gradute