Data Engineer (Snowflake & Kafka)

Core Technical Requirements

• Strong experience with Snowflake for data warehousing, including writing efficient SQL and managing schemas.
• Proficiency in Airflow for orchestration and workflow management.
• Hands-on experience with AWS services, particularly S3 for storage and Lambda for serverless processing.
• Familiarity with Kafka concepts (producers, consumers, topics) and ability to integrate with streaming data pipelines.
• Solid understanding of data modelling, ETL/ELT processes, and performance optimization.

Programming & Engineering Skills

• Proficiency in Python for data engineering tasks and automation.
• Ability to design and implement scalable, maintainable data pipelines.
• Experience with version control systems (eg, Git) and collaborative development workflows.

Leadership & Mentorship

• Ability to lead technical initiatives within the team and drive best practices.
• Experience in mentoring junior engineers, providing guidance on coding standards, design patterns, and career development.
• Comfortable with code reviews and fostering a culture of continuous improvement.

Best Practices & Mindset

• Strong grasp of data quality principles, including validation and monitoring.
• Ability to read, understand, and refactor existing code effectively.
• Familiarity with CI/CD practices for data pipeline deployment.
• Comfortable working in cloud-native environments and following security/compliance standards.

Nice-to-Have

• Exposure to streaming data architectures and event-driven systems.
• Knowledge of Snowflake performance tuning and cost optimization.