Data Engineer

A premier, high-growth Israeli Medical AI & HealthTech scale-up engineering a life-saving artificial intelligence platform for real-time detection and clinical diagnosis of critical, time-sensitive medical conditions.

Deployed across leading global hospital networks and healthcare systems, the company's proprietary technology analyzes massive streams of clinical telemetry and imaging data in real time to accelerate triage and improve patient outcomes.

The company operates at substantial technological scale, tackling complex Big Data challenges, petabyte-scale data pipelines, and mission-critical cloud infrastructure.

Located in central Tel Aviv (walking distance from the train station), operating on a hybrid work model with 2 days WFH per week.

Role Description-

• Serving as a Staff / Principal Data Engineer, acting as a focal technical authority to lead data architecture, establish enterprise-grade methodologies, and drive cross-functional alignment across multiple engineering and AI research squads.

• Architecting, developing, and deploying resilient, petabyte-scale Data Pipelines, Streaming Platforms, and Lakehouse/Warehouse Architectures from scratch.

• Designing scalable real-time and batch data processing solutions using Python, Apache Spark, Kafka, and Databricks.

• Leading infrastructure-as-code and cloud data services on AWS using Terraform, integrating services such as EventBridge, SQS, SNS, DynamoDB, Kinesis, and S3.

• Optimizing query performance, data modeling, and storage efficiency across large-scale distributed databases and analytical data warehouses.

• Partnering closely with Data Scientists, ML Engineers, and Backend teams to enable low-latency access to high-fidelity medical telemetry and structured clinical datasets.

Requirements-

• Extensive hands-on industry experience as a Data Engineer – Mandatory

• Proven background in Core Data Infrastructure & Architecture, with experience designing high-scale distributed data platforms or building data platforms from scratch – Mandatory

• Advanced programming and data manipulation skills in Python – Mandatory

• Expert-level proficiency in SQL, Complex Data Modeling, and Query Performance Optimization – Mandatory

• Hands-on production experience designing and managing Data Lakehouse / Data Warehouse architectures (e.g., Databricks, Snowflake, Redshift, Delta Lake) – Mandatory

• Strong experience with streaming and distributed computing engines (Apache Kafka, Spark, Databricks, AWS Kinesis) – Mandatory

• Deep, practical knowledge of the AWS Cloud Ecosystem & Infrastructure-as-Code (Terraform, S3, EventBridge, SQS, SNS, DynamoDB) – Mandatory

• Proven experience in cross-team technical leadership, mentoring, and setting engineering standards – Mandatory

• Background in regulated domains or high-throughput environments (HealthTech / MedTech, Cybersecurity, FinTech, AdTech) – Significant Advantage