✦ Luna Orbit — Data & Analytics

Senior Engineer, Technology I

at AbbVie

📍 Mettawa, IL Unknown Posted March 27, 2026
Type Not Specified
Experience mid
Exp. Years 4+ years
Education Bachelor's Degree with 6 years' experience; Master's Degree with 5 years' experience; PhD with 0 years' experience
Category Data & Analytics

Mid-level data engineer responsible for designing and maintaining data pipelines, supporting big data initiatives, and collaborating across teams to enable data-driven decision making.

  • Build data pipelines
  • Develop ETL processes
  • Collaborate with analytics teams
  • Optimize data workflows
  • Support data infrastructure

Focus on data pipeline development using PySpark, Python, SQL, on AWS cloud platform, with experience in data modeling and big data processing.

The ideal candidate is a mid-level data engineer with 4+ years of experience in building data pipelines, ETL processes, and working with big data platforms like AWS and PySpark. They are collaborative, problem-solvers with strong communication skills.

Experience in data engineeringETL developmentBig Data platformsPython programmingCloud platformsData modeling
Pharmaceutical industry experienceAWS certificationData warehousingDevOps practices
PySparkPythonSQLAWSJiraConfluenceGit
Data EngineeringETLBig DataPysparkPythonSQLData PipelinesAWSData Modeling
Data EngineeringData PipelinesETLBig DataPySparkPythonSQLData ModelingAWSJiraConfluenceGit
Problem-solvingCollaborationCommunicationTeamworkTime Management

Preferred

AWS Certified Data AnalyticsAWS Solutions Architect
Industry Pharmaceutical / Life Sciences
Job Function Design and maintain data pipelines for analytics and data management
Role Subtype Data Engineer
Tech Domains Python, SQL, AWS, Jira, Confluence, Git
data engineeringetlbig datapysparkpythonsqldata pipelinesawscloud platformsdata modelingpharmaceuticalconfluencejiragitdata warehousingdevops

Less than 4 years of data engineering experience, Lack of experience with ETL or big data, No experience with cloud platforms, Inability to work in a team environment, No knowledge of data modeling

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