AWS Data Engineer – Build Scalable Data Lakehouse Solutions

About the role

We are looking for an experienced AWS Data Engineer to design and implement scalable data platforms and modern Data Lakehouse solutions on Amazon Web Services. The role involves working with large‑scale data pipelines, real‑time streaming, and advanced analytics in a fast‑moving, Agile environment.

Key responsibilities

• Develop and maintain end‑to‑end ETL/ELT pipelines using AWS Glue, EMR, and Spark.
• Design data models and optimize data flows for performance and cost efficiency.
• Implement Data Lakehouse architecture with Apache Iceberg and integrate with DynamoDB, PostgreSQL, Redshift, and Aurora.
• Build event‑driven workflows using Step Functions, Lambda, and EventBridge.
• Collaborate with data scientists to support ML data pipelines and real‑time analytics.

Required profile

• 5+ years of professional Data Engineering experience.
• 3+ years of hands‑on experience with AWS Big Data services.
• Strong background in distributed processing and Agile development.
• Bachelor’s degree in Computer Science, Engineering, or a related field.

Required skills

• AWS EMR, AWS Glue, AWS Step Functions, AWS Lambda, AWS EventBridge
• Apache Spark, PySpark, Spark Programming
• Python
• DynamoDB, PostgreSQL, Redshift, Aurora
• Apache Iceberg, Data Lakehouse Architecture
• ETL/ELT pipeline development, Data Modeling, Pipeline Optimization

What we offer

• Opportunity to work on cutting‑edge data platforms in a collaborative, remote‑friendly environment.
• Exposure to advanced AWS services and real‑time streaming technologies.