AWS Data Engineer

Programmers.io; Malvern (Chester County); On-site; USD 110,000 - 160,000; Full time

Job summary

Programmers.io is seeking an experienced AWS Data Engineer to design, build, and maintain scalable ETL pipelines within the AWS ecosystem. You will leverage AWS Lambda, Redshift, S3, Athena, and Glue, using Python and PySpark to transform and analyze large datasets.

You will collaborate with cross-functional teams to ensure data requirements are met, implement automation, monitor pipelines, and focus on performance, reliability, and cost efficiency in a fast-paced environment.

Qualifications

• 10+ years of experience in data engineering or similar roles.
• Hands-on with AWS data services and serverless architectures.
• Proficiency in Python and PySpark for data transformations.
• Experience delivering scalable ETL pipelines in cloud environments.

Responsibilities

• Design, develop, and maintain ETL workflows to load data into AWS Redshift and other cloud systems.
• Leverage AWS Lambda for real-time data processing and automation.
• Work with S3, Redshift, Athena, and Glue to support data pipelines.
• Use Python and PySpark to optimize data transformation logic and queries.
• Collaborate with cross-functional teams to understand data requirements and deliver solutions.
• Monitor and optimize cloud-based infrastructure for performance, reliability, and cost efficiency.

Skills

ETL design

Cloud architecture

Data modeling

Problem solving

Agile working

Tools

Git

CI/CD

AWS CloudFormation

S3

Athena

Glue

Redshift

Job description

Overview: We are seeking an experienced AWS Data Engineer with expertise in ETL processes, AWS Lambda, Redshift, and proficiency in Python and PySpark. This role requires hands‑on experience with cloud-based architecture, data engineering, and working with large-scale data processing systems. The ideal candidate will play a critical role in building and maintaining scalable, efficient, and secure ETL pipelines within the AWS ecosystem.

Key Responsibilities:

• Design, develop, and maintain robust ETL workflows to extract, transform, and load data from various sources to AWS Redshift and other cloud-based systems.
• Leverage AWS Lambda to build serverless computing solutions for real-time data processing and automation.
• Work with AWS data storage and processing services, including S3, Redshift, Athena, and Glue, to support data processing pipelines.
• Utilize Python and PySpark to create and optimize data transformation logic and analytical queries.
• Collaborate with cross‑functional teams to understand data requirements and provide efficient data solutions.
• Monitor and optimize cloud-based infrastructure for performance, reliability, and cost efficiency.
• Troubleshoot and resolve data pipeline issues, ensuring minimal downtime and high data accuracy.
• Implement automation and monitoring tools to enhance reliability.

Required Skills and Qualifications:

• Proven experience working with AWS services, including Lambda, Redshift, S3, Athena, Glue, and CloudWatch.
• Strong knowledge and hands‑on experience with Python and PySpark for data transformation and processing.
• Expertise in building and optimizing ETL pipelines in a cloud environment.
• In‑depth understanding of relational databases, data warehousing, and performance tuning in Redshift.
• Strong problem‑solving and troubleshooting skills.
• Familiarity with infrastructure as code tools like AWS CloudFormation.
• Experience with version control (e.g., Git) and CI/CD pipelines.
• Solid understanding of data security, data privacy, and compliance frameworks.
• Ability to work in an agile, fast‑paced environment.

Skills: Digital : Python~Digital : Amazon Web Service(AWS) Cloud Computing~Core Java| GUI & Rich Clients~Core Java

Experience Required: 10 & Above