✦ Luna Orbit — Data & Analytics

Data Engineer I, Data : Science Engineering, AWS Marketing

at Amazon.com

📍 US, WA, Seattle Unknown Posted March 26, 2026
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Position Details

Type Not Specified
Experience entry
Exp. Years 0+ years
Education Not specified
Category Data & Analytics

About this role

This role involves developing and maintaining automated data pipelines using AWS services, ensuring data quality, security, and reliability for marketing analytics.

Key Responsibilities

  • Develop ETL pipelines
  • Maintain data quality frameworks
  • Implement data security measures
  • Collaborate with science teams
  • Optimize data infrastructure

Technical Overview

Focus on building scalable ETL/ELT pipelines with Python, Spark, and AWS tools like Redshift, S3, Lambda, and SageMaker, supporting data-driven marketing initiatives.

Ideal Candidate

The ideal candidate is an entry-level data engineer with foundational skills in ETL, Python, SQL, and AWS services, eager to build and maintain scalable data pipelines and infrastructure within a collaborative environment.

Must-Have Skills

ETL pipelinesPythonSQLAWS services

Nice-to-Have Skills

SparkRedshiftS3GlueLambdaSageMakerStep FunctionsSNSCloudWatchData quality frameworksData security

Tools & Platforms

RedshiftS3GlueLambdaSageMakerStep FunctionsSNSCloudWatch

Required Skills

ETL pipelinesPythonSparkSQLAWS servicesRedshiftS3GlueLambdaSageMaker

Hard Skills

ETL pipelinesPythonSparkSQLAWS servicesRedshiftS3GlueLambdaSageMakerStep FunctionsSNSCloudWatchData quality frameworksData securityData governance

Soft Skills

OwnershipCollaborationProblem-solvingData-driven decision makingCommunication

Industry & Role

Industry Technology
Job Function Building and maintaining cloud-based marketing data pipelines
Role Subtype Data & Analytics
Tech Domains Amazon Web Services, Redshift, S3, AWS Lambda, SageMaker, Glue, Step Functions, CloudWatch

Keywords for Your Resume

ETL pipelinesPythonSparkSQLAWSRedshiftS3GlueLambdaSageMakerStep FunctionsSNSCloudWatchData qualityData securityData governanceData pipelinesData automationData infrastructure

Deal Breakers

Lack of experience with ETL pipelines or Python, No familiarity with AWS services, Inability to work with data security or governance frameworks

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