Remote Senior AWS Data Engineer — Scalable Data Pipelines

Sequoia Connect; Atlanta (GA); On-site; USD 140,000 - 190,000; Full time

Job summary

Sequoia Connect is seeking a Senior AWS Data Engineer to design and optimize scalable ETL pipelines using Python, PySpark, and AWS services. You will work on data lake and warehouse solutions, ensuring data quality and efficient transformations in a dynamic, automation-focused environment.

You will collaborate with global teams, implement monitoring and governance, and mentor junior engineers. This remote role offers opportunities across delivery centers and cloud-native modernization

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

Data engineering

ETL

Education

Bachelor's degree or higher

Tools

AWS Glue

Redshift

RDS

Lambda

Step Functions

SNS

SQS

S3

Athena

EMR

CloudWatch

CloudTrail

GitLab

Terraform

CI/CD

Job description

Sequoia Connect is seeking a Senior AWS Data Engineer to design and optimize scalable ETL pipelines using Python, PySpark, and AWS services. You will work on data lake and warehouse solutions, ensuring data quality and efficient transformations in a dynamic, automation-focused environment.

You will collaborate with global teams, implement monitoring and governance, and mentor junior engineers. This remote role offers opportunities across delivery centers and cloud-native modernization