DataOps Engineer

We are a market-leading B2C live-streaming platform with over 450 million registered users. In an industry projected to reach $240 billion in the coming years, we are pushing the limits to remain the global leader in high-quality video technology.

Our team is a high-energy mix of creative thinkers, overachievers, and tech enthusiasts. We operate in a fast-paced culture of growth where we tackle "impossible" challenges to support millions of creators worldwide.

Role Overview

As a DataOps Engineer, you will bridge the gap between development and operations. You will architect scalable infrastructure, automate complex data lifecycles, and ensure the reliability of our massive data ecosystem. This is a mid-level, full-time position based in Tel Aviv.

Core Responsibilities

• Infrastructure & Architecture: Architect and maintain scalable cloud-based data infrastructure including compute, storage, and messaging.
• Automation: Implement Infrastructure-as-Code (Terraform) and develop internal tooling for deployment automation and testing frameworks.
• Pipeline Operations: Collaborate with Data Engineering to operationalize new pipelines, frameworks, and data models.
• Observability: Own uptime and performance; implement monitoring, alerting, and logging using modern observability platforms.
• Quality & Reliability: Champion data quality and lineage tracking while leading incident response and root-cause analysis.
• Leadership: Guide architectural reviews, mentor junior engineers, and contribute to the long-term data platform strategy.
  
  

• Experience: 3-5+ years in DataOps, DevOps, or a similar engineering role.
• Cloud Ecosystems: Strong hands-on experience with GCP, AWS, or Azure.
• Technical Stack:
• Orchestration: Airflow or Cloud Composer.
• Messaging: Kafka, Pub/Sub, or similar.
• Processing: Apache Beam, Spark, or Flink.
• Tooling: Terraform, Docker, and CI/CD pipelines.
• Languages: Proficiency in Python and SQL for automation.
• Operational Excellence: Proven track record of managing production-grade platforms with a focus on SLAs and cost optimization.
  

• GCP Expertise: Deep experience with BigQuery, Dataflow, Dataplex, or Cloud Composer.
• BI & ML: Familiarity with Looker or ML Ops/model lifecycle management.
• Real-time Processing: Expertise in performance tuning for Kafka or Flink.