Java Software Engineer
Posted 24 days ago · 0 applicants
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The role in plain words
This role involves joining the core Data Infrastructure team to design, scale, and maintain high-throughput data pipelines that process real-time medical telemetry and clinical images. You will write code using Python and the JVM ecosystem, manage cloud infrastructure with Terraform, and collaborate with data science and backend teams to support highly available data platforms.
- 7 years of proven professional experience operating as a Data Engineer or Backend Software Engineer building enterprise-grade architectures
- Production-proven development mastery within the JVM ecosystem (Java, Scala, or Kotlin)
- Extensive, hands-on experience designing and operating distributed systems within Cloud environments (AWS preferred)
- Practical experience engineering large-scale, production-ready Data Pipelines or distributed stream processing engines (e.g., Spark, Kafka, Airflow)
Extracted from the job description · kept up to date automatically
Who this suits
This role suits experienced engineers with at least 7 years of backend or data engineering experience, particularly those with strong JVM development skills and hands-on experience with distributed cloud systems like AWS, Spark, or Kafka. It is less ideal for junior developers or those without production-level experience in large-scale data pipeline architectures.
Full job description
Original listing · kept for referenceAn established, high-growth Medical Tech enterprise that has engineered an AI-driven clinical intelligence platform capable of identifying critical, time-sensitive medical anomalies in real time to assist medical teams in life-saving decisions.
Deployed across major global healthcare institutions, the company’s platform processes massive streams of complex clinical data under strict uptime and regulatory standards.
The organization maintains a robust technological footprint, housing over 400 professionals globally.
The company's primary R&D center is located in Tel Aviv within short walking distance of the train station, operating under a flexible hybrid structure that supports two days of remote work per week.
Position Overview-
• Senior Data Infrastructure Engineer joining the core Data Infra cell responsible for architecting, scaling, and maintaining the company’s unified, high-throughput data processing ecosystem.
• Designing and building resilient, fault-tolerant data pipelines capable of handling high-velocity medical telemetry, multi-modal clinical images, and real-time streaming updates.
• Owning the foundational cloud infrastructure and automated infrastructure-as-code (IaC) deployment definitions to support highly available data platforms.
• Collaborating cross-functionally with Data Science, Backend Engineering, and Platform teams to deliver scalable data storage, extraction, and transformation capabilities.
• Core Stack & Ecosystem- Python, JVM Ecosystem (Java / Scala / Kotlin), AWS, Terraform, Distributed Streaming (Kafka, Kinesis), Big Data Processing (Spark), Orchestration & Transformation (Airflow, DBT), Messaging (EventBridge, SQS, SNS), and NoSQL/Object Storage (DynamoDB, S3).
Requirements-
• 7 years of proven professional experience operating as a Data Engineer or Backend Software Engineer building enterprise-grade architectures – Mandatory
• Production-proven development mastery within the JVM ecosystem (Java, Scala, or Kotlin) – Mandatory
• Extensive, hands-on experience designing and operating distributed systems within Cloud environments (AWS preferred) – Mandatory
• Practical experience engineering large-scale, production-ready Data Pipelines or distributed stream processing engines (e.g., Spark, Kafka, Airflow) – Mandatory
• Deep technical familiarity with automation, infrastructure-as-code (Terraform), and building highly resilient data layers – Significant Advantage
Questions about this role
- This listing did not state a salary. We only show pay when the employer publishes it.
- Hybrid
- 7 years of proven professional experience operating as a Data Engineer or Backend Software Engineer building enterprise-grade architectures, Production-proven development mastery within the JVM ecosystem (Java, Scala, or Kotlin), Extensive, hands-on experience designing and operating distributed systems within Cloud environments (AWS preferred), Practical experience engineering large-scale, production-ready Data Pipelines or distributed stream processing engines (e.g., Spark, Kafka, Airflow)