AWS Data Engineer

Job Overview :

We are looking for an experienced AWS Data Engineer to design, develop, and maintain scalable data pipelines and cloud-based data solutions on AWS. The ideal candidate should have strong expertise in data engineering, ETL/ELT, Python, SQL, and AWS data services, with experience working on large-scale data processing environments.

Key Responsibilities :

• Design, develop, and maintain scalable data pipelines and ETL/ELT workflows on AWS.
• Build and optimize data ingestion, transformation, and processing pipelines from structured and unstructured data sources.
• Develop data solutions using AWS services such as S3, Glue, Lambda, EMR, Redshift, Athena, Kinesis, and Step Functions.
• Develop and maintain data warehouses, data lakes, and lakehouse solutions on AWS.
• Write efficient and optimized SQL and Python code for data processing and transformation.
• Implement data quality, validation, monitoring, and error-handling mechanisms.
• Optimize data pipelines and queries for performance, scalability, and cost efficiency.
• Integrate data from multiple sources including databases, APIs, applications, and external systems.
• Work with architects, data scientists, analysts, and business stakeholders to understand data requirements.
• Implement security, access controls, encryption, and governance across AWS data environments.
• Troubleshoot pipeline failures, data issues, and production incidents.
• Develop automated workflows and deployment processes using CI/CD and Infrastructure as Code practices.
• Maintain technical documentation for data pipelines, architecture, data models, and processes.

Required Skills & Experience :

• Strong experience as an AWS Data Engineer or in a similar data engineering role.
• Hands-on experience with AWS data and analytics services.
• Strong proficiency in Python and SQL.
• Experience with AWS Glue, S3, Redshift, Athena, and Lambda.
• Strong understanding of ETL/ELT concepts and data pipeline architecture.
• Experience with data warehousing, data lakes, and large-scale data processing.
• Good understanding of relational and NoSQL databases.
• Experience with data modeling, data transformation, and data integration.
• Knowledge of AWS IAM, security, networking, and access-control concepts.
• Experience with Git and CI/CD practices.
• Strong problem-solving and analytical skills.