Senior AWS Data Engineer | PySpark, ETL & Data Pipelines

Interon IT Solutions; Chantilly (VA); On-site; USD 125,000 - 170,000; Full time

Job summary

Interon IT Solutions is seeking an experienced AWS Data Engineer to design, build, and support scalable data pipelines in a cloud environment. You will collaborate with engineering, analytics, and business teams to process large datasets and deliver reliable, production-ready data solutions.

Ideal candidates have 7+ years in data engineering, strong Python and PySpark skills, ETL development, and hands-on AWS experience, along with SQL and data modeling capabilities.

Qualifications

• 7+ years of data engineering experience.
• Strong hands-on experience with Python, PySpark, ETL, and AWS.
• Strong SQL and data-transformation skills.
• Experience processing large datasets in distributed environments.
• Understanding of data modeling and cloud-based data-pipeline architecture.
• Experience troubleshooting and supporting production data pipelines.
• Strong communication and problem-solving skills.

Responsibilities

• Design, develop, and maintain scalable ETL and data-processing pipelines.
• Build data-engineering solutions using Python and PySpark.
• Process and transform large structured and unstructured datasets.
• Develop cloud-based data solutions using AWS services.
• Monitor data pipelines and troubleshoot data-quality and performance issues.
• Optimize ETL workflows for reliability, scalability, and efficiency.
• Partner with application, analytics, and business teams to understand data requirements.
• Perform unit testing, code reviews, deployments, and production support.
• Follow data security, governance, and engineering best practices.
• Document technical designs, workflows, and operational procedures.

Skills

Python

PySpark

ETL

AWS

SQL

Data modeling

Distributed processing

Tools

Databricks

Job description

Interon IT Solutions is seeking an experienced AWS Data Engineer to design, build, and support scalable data pipelines in a cloud environment. You will collaborate with engineering, analytics, and business teams to process large datasets and deliver reliable, production-ready data solutions.

Ideal candidates have 7+ years in data engineering, strong Python and PySpark skills, ETL development, and hands-on AWS experience, along with SQL and data modeling capabilities.