Description

Build and manage data pipelines within an AWS environment.

Build and maintain scalable data pipelines using AWS services including S3, Redshift, RDS, Glue, EMR, and Lambda. Design and implement ETL processes and data warehousing solutions. Develop data models to support business requirements and apply big data technologies to process large datasets. Collaborate with team members to solve complex data engineering problems.

Responsibilities

• Design and implement ETL processes and data warehousing solutions.
• Build scalable data pipelines using AWS services including S3, Redshift, RDS, Glue, EMR, and Lambda.
• Develop and maintain data models to support business requirements.
• Apply big data technologies to process large datasets.
• Collaborate with team members to solve complex data engineering problems.

Required Skills

• 3+ years of experience in data engineering focused on AWS.
• Proficiency in Python and SQL.
• Hands-on experience with Hadoop, Spark, and Kafka.
• Strong understanding of data modeling and ETL workflows.
• Experience with AWS services: S3, Redshift, RDS, Glue, EMR, and Lambda.
• Bachelor's degree in Computer Science, Information Technology, or a related field.

Preferred Skills

• AWS certifications such as Data Analytics – Specialty or Solutions Architect.
• Familiarity with DevOps tools including CI/CD, Docker, and Kubernetes.

Key Skills

Education

Bachelor's degree in Computer Science