עדיין מחפשים עבודה במנועי חיפוש? הגיע הזמן להשתדרג!
במקום לעבור לבד על אלפי מודעות, Jobify מנתחת את קורות החיים שלך ומציגה לך רק משרות שבאמת מתאימות לך.
מעל 80,000 משרות • 4,000 חדשות ביום
חינם. בלי פרסומות. בלי אותיות קטנות.
מלאה
22,000-32,000 ₪
Responsibilities
Architect and maintain scalable cloud-based data infrastructure (compute, storage, orchestration, messaging, workflow management).
Collaborate closely with Data Engineering to operationalize new pipelines, frameworks, and data models.
Implement infrastructure-as-code (e.g., Terraform) to ensure consistent, automated environment provisioning.
Develop internal tooling to support deployment automation, testing frameworks, and pipeline lifecycle management.
Own reliability, uptime, and performance across all production data workflows.
Implement monitoring, alerting, logging, and traceability using modern observability platforms.
Champion data quality, lineage tracking, and automated validation frameworks.
Lead incident response, root-cause analysis, and postmortems for pipeline or platform issues.
Work daily with data engineers, analysts, platform engineers, and stakeholders to improve reliability and developer experience.
Lead architectural reviews and guide teams in adopting DataOps best practices.
Mentor junior engineers and contribute to long-term data platform strategy.
Maintain clear, consistent documentation of operational processes, infrastructure components, and standards.
Architect and maintain scalable cloud-based data infrastructure (compute, storage, orchestration, messaging, workflow management).
Collaborate closely with Data Engineering to operationalize new pipelines, frameworks, and data models.
Implement infrastructure-as-code (e.g., Terraform) to ensure consistent, automated environment provisioning.
Develop internal tooling to support deployment automation, testing frameworks, and pipeline lifecycle management.
Own reliability, uptime, and performance across all production data workflows.
Implement monitoring, alerting, logging, and traceability using modern observability platforms.
Champion data quality, lineage tracking, and automated validation frameworks.
Lead incident response, root-cause analysis, and postmortems for pipeline or platform issues.
Work daily with data engineers, analysts, platform engineers, and stakeholders to improve reliability and developer experience.
Lead architectural reviews and guide teams in adopting DataOps best practices.
Mentor junior engineers and contribute to long-term data platform strategy.
Maintain clear, consistent documentation of operational processes, infrastructure components, and standards.
Requirements:
Requirements:
3-5+ years in DevOps/DataOps Engineering, or similar roles.
Strong hands-on experience with modern cloud data ecosystems (GCP, AWS, Azure).
Deep understanding of:
Distributed Systems and Data Pipelines.
Orchestration frameworks (e.g., Airflow, Cloud Composer).
Streaming and messaging systems (Kafka, Pub/Sub, etc.).
Batch and streaming processing frameworks (e.g., Apache Beam, Spark, Flink).
Infrastructure-as-code (Terraform), containers (Docker), CI/CD tooling.
Python and SQL for automation and data workflow integration.
Experience operating production-grade data platforms with a strong focus on SLAs, reliability, and cost optimization.
Nice to Have:
Google Cloud Platform experience- especially BigQuery, Dataflow, Pub/Sub, Dataplex, or Cloud Composer- is a significant plus.
Experience with BI platforms such as Looker.
Familiarity with ML Ops/model lifecycle management.
Real-time data processing experience with Kafka, Flink, or similar.
Expertise in cost optimization and performance tuning for cloud-based data warehouses.
Requirements:
3-5+ years in DevOps/DataOps Engineering, or similar roles.
Strong hands-on experience with modern cloud data ecosystems (GCP, AWS, Azure).
Deep understanding of:
Distributed Systems and Data Pipelines.
Orchestration frameworks (e.g., Airflow, Cloud Composer).
Streaming and messaging systems (Kafka, Pub/Sub, etc.).
Batch and streaming processing frameworks (e.g., Apache Beam, Spark, Flink).
Infrastructure-as-code (Terraform), containers (Docker), CI/CD tooling.
Python and SQL for automation and data workflow integration.
Experience operating production-grade data platforms with a strong focus on SLAs, reliability, and cost optimization.
Nice to Have:
Google Cloud Platform experience- especially BigQuery, Dataflow, Pub/Sub, Dataplex, or Cloud Composer- is a significant plus.
Experience with BI platforms such as Looker.
Familiarity with ML Ops/model lifecycle management.
Real-time data processing experience with Kafka, Flink, or similar.
Expertise in cost optimization and performance tuning for cloud-based data warehouses.
This position is open to all candidates.
במקום לעבור לבד על אלפי מודעות, Jobify מנתחת את קורות החיים שלך ומציגה לך רק משרות שבאמת מתאימות לך.
מעל 80,000 משרות • 4,000 חדשות ביום
חינם. בלי פרסומות. בלי אותיות קטנות.
תל אביב - יפו
ערב
8 חודשים
תעודה ממשלתית
סבסוד
באר שבע
