Data Engineer (Diagnostic Solutions)
Company Background
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.
Project Description
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.
Technologies
- Python
- Databricks
- Apache Spark
- Hive
- AWS EMR
- S3
- Oracle SQL
- DataStage
- CI/CD tools
- Mainframe systems
What You'll Do
- 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 DataStage
- 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
Job Requirements
- 5+ years of experience in Data Engineering or related role
- 5+ 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 DevOps 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)
What Do We Offer
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;
- English courses;
- 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.
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