Senior AWS Data Engineer - Python & PySpark on Redshift

Ethereum Technologies; Reston (VA); On-site; USD 120,000 - 160,000; Full time

Job summary

ETHEREUM TECHNOLOGIES LLC is seeking a data engineer to build and maintain ETL pipelines using Python and PySpark on AWS Glue. You will orchestrate workflows with Step Functions, implement event-driven patterns with SNS/SQS, and optimize storage and querying in Redshift.

The role requires strong Python/PySpark skills, hands-on AWS experience, and solid SQL with data modeling. You will ensure data quality, monitoring, and contribute to CI/CD and IaC efforts in a collaborative environment.

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.
• Familiarity with version control (Git) and basic DevOps/CI-CD workflows.

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

SQL

Data modeling

ETL best practices

Monitoring/alerting

Git

CI/CD workflows

Tools

AWS Lambda

AWS SNS

AWS SQS

AWS Glue

Amazon Redshift

AWS Step Functions

Job description

ETHEREUM TECHNOLOGIES LLC is seeking a data engineer to build and maintain ETL pipelines using Python and PySpark on AWS Glue. You will orchestrate workflows with Step Functions, implement event-driven patterns with SNS/SQS, and optimize storage and querying in Redshift.

The role requires strong Python/PySpark skills, hands-on AWS experience, and solid SQL with data modeling. You will ensure data quality, monitoring, and contribute to CI/CD and IaC efforts in a collaborative environment.