AWS Data Engineer
First seen by Alion on Sep 28, 2026.
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.
Skills
AWS, Data Engineering, Data Pipeline, ETL, SQL, Python, AWS Lambda, Data Warehousing, AWS Glue