Senior AWS Data Engineer

United States Digital Space LLC; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

United States Digital Space LLC is seeking a Senior AWS Data Engineer to design, build, and optimize scalable ETL pipelines using Python, PySpark, and AWS services. You will develop workflows with Glue, Lambda, and Step Functions, and implement data lake/warehouse solutions with S3, Athena, and Redshift.

The role requires 8–12 years of software development experience, deep AWS expertise, and a strong background in data integration, with a remote-friendly, visa-friendly environment.

Qualifications

• :8–12 years of software development experience across the appropriate platform.
• Solid IT background and experience.
• Experience as an application developer for projects similar in scope and responsibility.
• Strong expertise in Python, PySpark, and SQL.
• Strong hands-on experience with AWS services such as Glue, Redshift, RDS, Lambda, Step Functions, SNS, SQS, S3, Athena, EMR, CloudWatch, and CloudTrail.
• Experience with enterprise data lakes, data warehouses, data marts, and big data environments.
• Strong understanding of ETL best practices, data quality, and operational support.
• Experience with APIs, JSON, and cloud-based data integration patterns.
• Familiarity with GitLab, Terraform, CI/CD, and AWS developer tools.
• Experience with DynamoDB, EC2, ECS and Batch.
• Exposure to data migration and cloud modernization programs.
• Have a good understanding of performance engineering of code pipelines and near real-time systems.
• Good understanding on Agents and MCP
• High-Performance Mindset: Resilience, emotional intelligence, and a focus on agile delivery.
• Technologist DNA: A deep understanding of the difference between "coding" and "engineering."

Responsibilities

• Design, build, and maintain scalable ETL and data pipelines using Python, PySpark, and AWS services.
• Develop and manage workflows using Glue, Lambda, and Step Functions.
• Build event-driven integrations using SNS, SQS, and related AWS services.
• Design and optimize data lake and warehouse solutions using S3, Athena, and Redshift.
• Write and tune high-performance SQL for complex transformations and reporting.
• Design and Implement data validation, monitoring, logging, alerting, and error-handling frameworks.
• Design and Support API-based and JSON-based integrations across internal and external systems.
• Troubleshoot operational issues, identify root causes, and implement corrective actions.
• Contribute to documentation, deployment automation, and engineering best practices.
• Collaborate with stakeholders and mentor junior team members where needed.

Skills

Python

PySpark

SQL

AWS services

Education

Degree holders for visa

Tools

Glue

Redshift

S3

Lambda

Step Functions

SNS

SQS

Athena

EMR

CloudWatch

CloudTrail

GitLab

Terraform

CI/CD

DynamoDB

EC2

ECS

Batch

Job description

At the company, we are a Talent-First Technology Ecosystem that redefines how elite professionals interact with the global digital landscape. We move beyond traditional models to act as a catalyst for the top 1% of global talent, connecting human potential with complex industrial execution. By joining our inner circle, you are not simply taking a position; you are aligning with a strategic partner dedicated to updating your "Human OS" and accelerating your growth through world-class, high-impact projects.

We are currently partnering with a rapidly growing, automation-led powerhouse that serves 31 Fortune 500 companies across the financial, healthcare, and manufacturing sectors. With a global workforce of over 32,000 employees and a presence in 28 countries, our client is a titan of digital transformation. Their "Automate Everything, Cloudify Everything" strategy ensures you will be working at the absolute forefront of AI-driven automation and cloud solutions.

This is your chance to thrive in a "Customer Success, First and Always" environment that prizes continuous learning and radical ownership. You will collaborate within an international network of expertise across 39 delivery centers worldwide, gaining exposure to complex engineering challenges that redefine industrial standards. If you are a driven professional looking for a dynamic, forward-thinking workplace where your growth is the priority, this is where you belong.

Senior AWS Data Engineer:

The Challenge (Responsibilities)

• Design, build, and maintain scalable ETL and data pipelines using Python, PySpark, and AWS services.
• Develop and manage workflows using Glue, Lambda, and Step Functions.
• Build event-driven integrations using SNS, SQS, and related AWS services.
• Design and optimize data lake and warehouse solutions using S3, Athena, and Redshift.
• Write and tune high-performance SQL for complex transformations and reporting.
• Design and Implement data validation, monitoring, logging, alerting, and error-handling frameworks.
• Design and Support API-based and JSON-based integrations across internal and external systems.
• Troubleshoot operational issues, identify root causes, and implement corrective actions.
• Contribute to documentation, deployment automation, and engineering best practices.
• Collaborate with stakeholders and mentor junior team members where needed.

Your Profile (Requirements)

• Degree holders for the visa application process.
• 8-12 years of software development experience across the appropriate platform.
• Solid IT background and experience.
• Experience as an application developer for projects similar in scope and responsibility.
• Strong expertise in Python, PySpark, and SQL.
• Strong hands-on experience with AWS services such as Glue, Redshift, RDS, Lambda, Step Functions, SNS, SQS, S3, Athena, EMR, CloudWatch, and CloudTrail.
• Experience with enterprise data lakes, data warehouses, data marts, and big data environments.
• Strong understanding of ETL best practices, data quality, and operational support.
• Experience with APIs, JSON, and cloud-based data integration patterns.
• Familiarity with GitLab, Terraform, CI/CD, and AWS developer tools.
• Experience with DynamoDB, EC2, ECS and Batch.
• Exposure to data migration and cloud modernization programs.
• Have a good understanding of performance engineering of code pipelines and near real-time systems.
• Good understanding of Agents and MCP.
• High-Performance Mindset: Resilience, emotional intelligence, and a focus on agile delivery.
• Technologist DNA: A deep understanding of the difference between "coding" and "engineering."

Desired

• Familiarity with cloud-native foundations or AI coding assistants.

Languages

• Advanced Oral English: For seamless collaboration with global teams.
• Advanced Spanish.

Special Notes

• N/A

Work Arrangement

We value flexibility to support your lifestyle. This position is available as:

• Remote

Requirements:

• 8-12 years of software development experience across the appropriate platform.
• Solid IT background and experience.
• Experience as an application developer for projects similar in scope and responsibility.
• Strong expertise in Python, PySpark, and SQL.
• Strong hands-on experience with AWS services such as Glue, Redshift, RDS, Lambda, Step Functions, SNS, SQS, S3, Athena, EMR, CloudWatch, and CloudTrail.
• Experience with enterprise data lakes, data warehouses, data marts, and big data environments.
• Strong understanding of ETL best practices, data quality, and operational support.
• Experience with APIs, JSON, and cloud-based data integration patterns.
• Familiarity with GitLab, Terraform, CI/CD, and AWS developer tools.
• Experience with DynamoDB, EC2, ECS and Batch.
• Exposure to data migration and cloud modernization programs.
• Have a good understanding of performance engineering of code pipelines and near real-time systems.
• Good understanding on Agents and MCP

Keywords:

Python, PySpark, AWS, ETL, SQL