Data Engineer; Diagnostic Solutions

The customer is a global leader in diagnostics and drug development, employing over 70,000 professionals and serving clients in more than 100 countries. With over $14 billion in annual revenue, they are committed to advancing healthcare and empowering patients, providers, and researchers through data-driven solutions. Their mission is to improve health and improve lives by delivering clear and confident answers in a complex medical landscape.

The project involves building a new internal system to support Laboratory Information Management (LIM). The goal is to modernize and streamline data handling processes, improve data accessibility, and enhance performance across large-scale data workflows. The team is responsible for both designing and implementing a high-performance solution, working closely with the client on architecture decisions, performance tuning, and best practices in data engineering.

• Python
• Databricks
• Hive
• AWS EMR
• S3
• Oracle SQL
• Data Stage
• CI/CD tools
• Mainframe systems

• Design and implement scalable data processing pipelines using Spark, Hive, and Python
• Collaborate with stakeholders on system architecture, performance tuning, and design decisions
• Optimize SQL and Spark queries to ensure fast and efficient data access
• Develop ETL processes and manage data flow across systems using tools like Data Stage
• Contribute to the CI/CD pipeline setup, automation, and deployment strategies
• Participate in code reviews, documentation, and cross-functional planning meetings
• Support the data modeling process within a data warehouse environment
• Work collaboratively with the client's engineering and architecture teams

• 4+ years of experience in Data Engineering or related role
• 4+ years of hands-on Python development experience
• Experience with Databricks, Spark, Hive, AWS EMR/S3
• Proficiency in Oracle SQL and query tuning
• Familiarity with CI/CD tools and modern Dev Ops practices
• Strong understanding of SDLC and software engineering principles
• Experience with data modeling and ETL in large-scale environments
• Exposure to mainframe systems is a plus
• English level: B1+ (spoken and written)

The global benefits package includes:

• Technical and non-technical training for professional and personal growth;
• Internal conferences and meetups to learn from industry experts;
• Support and mentorship from an experienced employee to help you professional grow and development;
• Internal startup incubator;
• Health insurance;
• Sports activities to promote a healthy lifestyle;
• Flexible work options, including remote and hybrid opportunities;
• Referral program for bringing in new talent;
• Work anniversary program and additional vacation days.