Data Engineer

• Design and implement scalable ETL pipelines using PySpark on AWS
• Develop and optimize data workflows for Snowflake integration
• Manage and configure AWS services such as S3, Lambda, Glue, EMR, and Redshift
• Collaborate with data analysts and business teams to understand requirements and deliver solutions
• Ensure data security and compliance with best practices in AWS and Snowflake environments
• Monitor and troubleshoot data pipelines and workflows for performance and reliability
• Write efficient, reusable, and maintainable code for data processing and transformation.

• Strong experience with AWS services (S3, Lambda, Glue, MSK, etc.)
• Proficiency in PySpark for large-scale data processing
• Hands-on experience with Snowflake for data warehousing and analytics
• Solid understanding of SQL and database optimization techniques
• Knowledge of data lake and data warehouse architectures
• Familiarity with CI/CD pipelines and version control systems (e.g., Git)
• Strong problem-solving and debugging skills
• Experience with Terraform or CloudFormation for infrastructure as code
• Knowledge of Python for scripting and automation
• Familiarity with Apache Airflow for workflow orchestration
• Understanding of data governance and security best practices
• Certification in AWS or Snowflake is a plus.

Certification in AWS or Snowflake.

• Equal opportunity employer policies
• Accessibility and accommodations for persons with disabilities.