✦ Luna Orbit — Data & Analytics

Software Development Engineer - II, AWS Data Processing and Analytics team

at Amazon.com

📍 US, CA, East Palo Alto Unknown Posted March 17, 2026
Type Full-Time
Experience mid
Exp. Years 3+ years
Education Not specified
Category Data & Analytics

This role involves developing scalable data pipelines and managing data infrastructure for analytics at AWS. The engineer will work on big data processing, leveraging cloud services and distributed systems to enable real-time insights.

  • Build data pipelines
  • Manage data infrastructure
  • Implement data transformation
  • Collaborate on system architecture
  • Support analytics initiatives

Focus on data engineering, cloud data processing, AWS services, distributed systems, data pipelines, and serverless architectures.

The ideal candidate is a mid-level data engineer with 3+ years of experience in building scalable data pipelines, working with distributed systems, and leveraging AWS cloud services. They should be proficient in Python and familiar with serverless architectures and data transformation techniques.

PythonApache SparkData PipelinesAWSDistributed Systems
Serverless ComputingKinesisS3RedshiftSageMakerTerraformCDC
AWSS3RedshiftKinesisSageMakerTerraform
PythonApache SparkServerless ComputingDistributed SystemsData PipelinesData TransformationAWSKinesisS3RedshiftSageMakerTerraformCDC
PythonApache SparkServerless ComputingDistributed SystemsData PipelinesData TransformationAWSKinesisS3RedshiftSageMakerTerraformCDC
CommunicationLeadershipProblem-solvingCollaborationCreativity
Industry Technology / Cloud Data Processing
Job Function Data pipeline development and data infrastructure management for analytics
Role Subtype Data Engineer
Tech Domains Python, Apache Spark, AWS, Kinesis, S3, Redshift, SageMaker, Terraform
PythonApache SparkServerless ComputingDistributed SystemsData PipelinesData TransformationAWSKinesisS3RedshiftSageMakerTerraformCDCData EngineerData ProcessingBig DataCloud ComputingData AnalyticsData InfrastructureETL

Lack of experience with AWS services, No proficiency in Python, No experience with distributed systems or data pipelines

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