AWS Data Engineer

Education Requirements:

Bachelor Degree or equivalent in Computer Science, Information Systems or related

Roles & Responsibilities:

• Design and implement data pipelines using AWS services (Glue, Lambda, Kinesis, Step Functions, EMR, Data Pipeline) for ingestion, transformation, and processing of large-scale datasets.
• Develop and optimize ETL/ELT processes for structured and unstructured data using AWS Glue, PySpark, and SQL.
• Manage data storage solutions in AWS (S3, Redshift, DynamoDB, RDS, Aurora) ensuring scalability & performance.
• Implement data lake and data warehouse architectures on AWS using S3, Redshift, Lake Formation, and Athena.
• Build real-time and batch data processing solutions leveraging Amazon Kinesis, Kafka on AWS, and Spark on EMR.
• Ensure data quality and governance by applying data validation, cataloging and monitoring techniques
• Work with DevOps practices to deploy, monitor, and manage data pipelines using CI/CD tools.
• Optimize performance by applying partitioning, compression, and lifecycle policies.
• Ensure security and compliance by implementing IAM roles, encryption (KMS), VPC, and access control.
• Collaborate with data scientists, analysts, and business teams to provide high-quality datasets for analytics needs.
• Monitor and troubleshoot production data pipelines using CloudWatch, CloudTrail, and logging frameworks.
• Contribute to best practices & documentation to improve data engineering standards and team efficiency.