What you will do:

• Design, develop, and maintain scalable data pipelines and ETL processes leveraging AWS services such as S3, Glue, EMR, Lambda, and Redshift.
• Collaborate with data scientists and analysts to understand data requirements and implement solutions that support analytics and machine learning initiatives.
• Optimize data storage and retrieval mechanisms to ensure performance, reliability, and cost-effectiveness.
• Implement data governance and security best practices to ensure compliance and data integrity.
• Troubleshoot and debug data pipeline issues, providing timely resolution and proactive monitoring.
• Stay abreast of emerging technologies and industry trends, recommending innovative solutions to enhance data engineering capabilities.

What makes you a great fit:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 3-6 years of prior experience in data engineering, with a focus on designing and building data pipelines.
• Proficiency in AWS services, particularly S3, Glue, EMR, Lambda, and Redshift.
• Strong programming skills in languages such as Python, Java, or Scala.
• Experience with SQL and NoSQL databases, data warehousing concepts, and big data technologies.
• Familiarity with containerization technologies (e.g., Docker, Kubernetes) and orchestration tools (e.g., Apache Airflow) is a plus.