Senior AWS Data Engineer

Remote (United States)

Overview

This opportunity is for a Senior AWS Data Engineer to design, build, and optimize large-scale data platforms in a fully remote (United States) environment. This full-time role focuses on developing high-performance data pipelines, modern lakehouse architectures, and scalable cloud-native solutions to support analytics and reporting.

The role involves working with distributed data systems, implementing enterprise-grade ETL/ELT workflows, and ensuring data reliability, governance, and performance across complex environments.

Compensation

Base salary range: $145,000–$160,000 per year.

What You’ll Do

• Build and maintain scalable data pipelines on AWS to support ingestion, transformation, and enrichment of structured and semi-structured data.
• Design and implement Delta Lake tables optimized for ACID compliance, schema enforcement, partition pruning, and query performance.
• Develop ETL and ELT workflows that integrate multiple source systems into centralized, query-optimized data warehouse architectures.
• Apply business logic through dimensional modeling, joins, and aggregation aligned with data warehouse best practices.
• Collaborate with engineering teams to design and deploy cloud-native data solutions using AWS services such as S3, Glue, RDS, and IAM.
• Optimize pipeline performance using partitioning strategies, caching techniques, broadcast joins, and adaptive query tuning.
• Deploy and manage data engineering assets using Git-based workflows and CI/CD tools such as GitLab or Jenkins.
• Monitor pipeline health, job execution, and system performance using AWS CloudWatch and related monitoring tools.
• Conduct technical discovery of legacy systems and design end-to-end data flows for modernization initiatives.
• Implement data governance practices including metadata management, data quality validation, audit logging, and lineage tracking.
• Support ad hoc data access needs and develop reusable datasets and shared assets for analytics teams.

Qualifications

• 8+ years of experience in data engineering, analytics engineering, or related fields.
• 5+ years of experience building scalable ETL and ELT pipelines for reporting and analytics.
• 3+ years of experience developing enterprise data solutions in cloud environments, preferably AWS.
• Hands-on experience with Spark, Delta Lake, and distributed data processing frameworks.
• Strong experience with AWS services including S3, Glue, RDS, Step Functions, and IAM.
• Experience with Spark SQL-based data transformations and S3 partitioning strategies.
• Experience orchestrating workflows using tools such as Step Functions.
• Proficiency in infrastructure as code tools such as Terraform or AWS CloudFormation.
• Experience with CI/CD pipelines for deploying data engineering workloads.
• Strong understanding of data quality frameworks, validation techniques, and storage optimization strategies.
• Bachelor’s degree in a relevant technical field.
• Excellent communication and organizational skills.
• U.S. citizenship required.
• Ability to obtain or hold a DoD Public Trust Clearance.

Preferred Qualifications

• Experience building data pipelines with Spark using Java or Scala.
• Strong Java development experience in enterprise environments.

Additional Information

This is a remote U.S.-based position supporting federal initiatives. Candidates must meet all eligibility and clearance requirements.