Sr. AWS Data Engineer

Key Responsibilities:

• Design and develop scalable data architecture using AWS services such as S3, Redshift, Aurora, and Glue
• Implement and manage data pipelines to automate the extraction, transformation, and loading (ETL) processes
• Develop and optimize data models and data warehouse solutions that support analytical needs
• Collaborate with cross-functional teams to gather data requirements and translate them into actionable data solutions
• Monitor data pipeline performance and troubleshoot issues to ensure the reliability and accuracy of data
• Implement data governance practices to maintain data quality and integrity
• Stay current with evolving AWS technologies and industry trends to provide recommendations for improvements
• Mentor junior data engineers and help them grow their technical expertise in AWS data engineering
  

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field
• 8+ years of experience in data engineering with a focus on AWS technologies
• Strong experience of AWS services (S3, Redshift, Glue, Kinesis, Lambda, and more)
• Proficiency in Python, SQL, and ETL tools for data processing and transformation
• Experience designing data workflows and pipelines using AWS Glue or similar ETL tools
• Terraform, Liquibase, Bitbucket, Ancilary AWS services ( Secrets Manager, KMS, etc.),
• Solid knowledge of data warehousing concepts and data modeling techniques
• Familiarity with Apache Spark, Kafka, or other data streaming technologies is a plus
• Excellent communication skills and an ability to collaborate with technical and non-technical stakeholders
• A proactive approach to problem-solving and a strong desire to learn and grow
• AWS certifications (e.g., AWS Certified Data Analytics, AWS Certified Solutions Architect) are a plus
  

Benefits