✦ Luna Orbit — Data & Analytics

Professional Data Engineer

at Freddie Mac

Unknown 💰 $109K – $163K USD / year Posted March 28, 2026
Salary $109K – $163K USD / year
Type Full-Time
Experience mid
Exp. Years 2+ years
Education Not specified
Category Data & Analytics

This role involves developing and maintaining data pipelines on AWS and Snowflake, supporting data-driven decision-making through automation and scalable data solutions.

  • Build and support ETL pipelines
  • Automate data workflows
  • Collaborate on data integration
  • Support production data systems
  • Improve data pipeline quality

The technical environment includes AWS cloud services, Snowflake data platform, Python and Java programming, and ETL/ELT pipeline development for scalable data engineering.

The ideal candidate is a mid-level data engineer with experience in AWS, Snowflake, and building ETL/ELT pipelines, with strong programming skills in Python and Java, and a focus on automation and data pipelines.

PythonAWSSnowflakeETL/ELT pipelinesData pipelinesAutomationSoftware development
JavaTestingProduction supportData engineeringCloud experience
AWSSnowflakeJavaPython
PythonAWSSnowflakeETL pipelinesdata pipelinesautomationJavasoftware development
Data EngineeringAWSAmazon Web ServicesSnowflakePythonJavaETL/ELT pipelinesData pipelinesAutomationSoftware developmentTestingProduction support
CollaborationCommunicationProblem-solvingContinuous improvementTeamwork
Industry Financial Services / Banking
Job Function Developing scalable data pipelines and supporting data infrastructure
Role Subtype Data Engineer
Tech Domains Amazon Web Services, Snowflake, Python, Java
Data EngineerAWSAmazon Web ServicesSnowflakePythonJavaETL pipelinesData pipelinesAutomationSoftware developmentTestingProduction supportdata engineerawssnowflakeetl pipelinespythonjavaautomationsoftware developmentdata pipelinesproduction support

Lack of experience with AWS or Snowflake, No programming skills in Python or Java, No experience with ETL pipelines, Unfamiliar with data pipeline automation, No background in data engineering

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