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Lead Data Engineer
HybridFull-timeData EngineeringMedical DevicesHealthcare Software
A healthcare AI company is seeking a Lead Data Engineer to shape enterprise data architecture, build mission-critical infrastructure, and establish engineering practices for high-volume clinical telemetry. The role is based in Tel Aviv with a hybrid schedule including two work-from-home days per** [
Responsibilities
- Define data architectures and lead complex, cross-functional data engineering initiatives.
- Build and operate high-throughput data infrastructure and streaming and batch pipelines for large-scale clinical telemetry.
- Solve scalability, latency, and reliability challenges across distributed data frameworks and processing clusters.
- Design data lakehouse and data warehouse architectures for low-latency analytics and clinical AI model training.
- Partner with data science, clinical research, and backend engineering teams to productionize machine learning pipelines.
- Drive Infrastructure as Code, observability, data governance, and automated CI/CD practices across cloud environments.
Requirements
- At least 8 years of hands-on data engineering experience.
- Expertise in data infrastructure design, distributed systems architecture, and enterprise data platforms.
- Advanced Python programming and scripting skills.
- Advanced SQL development and complex query optimization experience.
- Hands-on experience designing, modeling, and maintaining data lakehouse or cloud data warehouse solutions.
Nice to have
- Experience with AWS services and distributed streaming or batch technologies such as Spark, Databricks, Kafka, Kinesis, EventBridge, DynamoDB, and S3.
- Experience with Terraform and containerized cloud workloads.