Senior AWS PySpark Data Engineer (ETL, Redshift)

MACHINE LEARNING TECHNOLOGIES LLC; Reston (VA); On-site; USD 83,000 - 131,000; Full time

Job summary

MACHINE LEARNING TECHNOLOGIES LLC is seeking a Sr AWS Python Developer to build data pipelines and analytics solutions in Reston, VA. You will design, implement, and optimize ETL processes on AWS using Python, PySpark, Lambda, Glue, and Redshift, delivering scalable data workflows that support business intelligence needs.

Collaborate with data engineers and stakeholders, contribute to CI/CD and IaC practices, write clean SQL for transformations, and ensure reliability with monitoring, error

Qualifications

• Strong experience with Python and PySpark for large-scale data processing.
• Hands-on experience with AWS services: Lambda, SNS, SQS, Glue, Redshift, Step Functions.
• Solid SQL skills and familiarity with data modeling and query optimization.
• Experience with ETL best practices, data quality checks, and monitoring/alerting.

Responsibilities

• Build and maintain ETL pipelines using Python and PySpark on AWS Glue and other compute platforms
• Orchestrate workflows with AWS Step Functions and serverless components (Lambda)
• Implement messaging and event-driven patterns using AWS SNS and SQS
• Design and optimize data storage and querying in Amazon Redshift
• Write performant SQL for data transformations, validation, and reporting
• Ensure data quality, monitoring, error handling and operational support for pipelines
• Collaborate with data consumers, engineers, and stakeholders to translate requirements into solutions
• Contribute to CI/CD, infrastructure-as-code, and documentation for reproducible deployments

Skills

Python

PySpark

AWS

SQL

ETL

Data modeling

CI/CD

Git

Lambda

Step Functions

Redshift

SQS

SNS

Glue

Spark

Job description

MACHINE LEARNING TECHNOLOGIES LLC is seeking a Sr AWS Python Developer to build data pipelines and analytics solutions in Reston, VA. You will design, implement, and optimize ETL processes on AWS using Python, PySpark, Lambda, Glue, and Redshift, delivering scalable data workflows that support business intelligence needs.

Collaborate with data engineers and stakeholders, contribute to CI/CD and IaC practices, write clean SQL for transformations, and ensure reliability with monitoring, error