Data Engineer

Eitan Medical is a fast-growing global medical device company, developing and manufacturing innovative drug delivery and infusion solutions across the continuum of care - from the hospital to the home. We are looking for an excellent Data Engineer to join the winning team!

Job Description

Eitan Medical is looking to hire a highly skilled and experienced professional to fill the role of Data Engineer. In this role, you will design, build, and maintain the data infrastructure that powers analytics, product innovation, and business decision-making across the organization. You will work closely with data scientists, data analysts, software engineers, product managers, and other teams to ensure reliable, secure and scalable access to data.

We are seeking a detail-oriented professional with strong problem-solving skills, a passion for working with complex real-world data, and the drive to contribute to meaningful innovations in healthcare. We are looking for someone who is self-driven, brings a “can-do” spirit, and thrives in a collaborative, fast-paced environment where teamwork and clear communication are essential.

Job Responsibilities:

• Design, develop, and maintain scalable ETL/ELT pipelines for ingesting, processing, and storing data from multiple sources
• Build and optimize data warehouses, data lakes, and other storage solutions to support analytics and machine learning use cases.
• Collaborate with data scientists and analysts to ensure datasets are clean, structured, and accessible for advanced modeling and reporting.
• Implement data quality monitoring, validation frameworks, and automated workflows to ensure reliability and accuracy.
• Integrate data from disparate systems into unified views that support business intelligence and operational efficiency.
• Ensure compliance with healthcare data regulations and implement security measures to safeguard company data and systems.
• Research and adopt best practices in data engineering, cloud-native architectures, and modern data tooling.
• Support the deployment of data-driven applications into production environments.
  
  

• 2–4 years of hands-on experience in data engineering or a related field.
• Proficiency in Python, SQL, and data pipeline frameworks (e.g., Airflow, dbt, Azure Data Factory).
• Experience with data warehouse technologies (e.g., Snowflake, BigQuery, Azure Synapse).
• Familiarity with cloud platforms (preferably Azure).
• Knowledge of data modeling, database design, and performance optimization.
• Experience building APIs or integrating data across different applications.
• Self learning ability and “Can do” attitude.
  
  

• Knowledge and hands-on experience with Elasticsearch for data indexing, search, and analytics.
• Familiarity with distributed data processing (e.g., Spark).
• Familiarity with event-driven architectures and streaming technologies (e.g., Kafka / RabbitMQ).
• Experience with NoSQL databases and engines (e.g., MongoDB, Redis).
• Experience with containerization and orchestration (e.g., Docker, Kubernetes).
• Background in healthcare or regulated environments (e.g., HIPAA, MDR, FDA).
  
  

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field – An Advantage.
  
  

• Fluent English - writing and verbal.