Senior Data Engineer

Cyera Cyera · Vertical AI · Tel Aviv, Israel · R&D

Senior Data Engineer to join the Research Engineering Team, responsible for designing, building, and scaling data infrastructure and pipelines to support AI model development and inference. The role involves collaborating with researchers and ML experts, optimizing data workflows, and managing cloud-based data platforms.

What you'd actually do

  1. Design and build scalable batch and streaming data pipelines that process complex datasets from diverse sources, enabling reliable and high-performance model training and inference.
  2. Collaborate closely with researchers and data scientists to deliver high-quality, structured datasets that accelerate experimentation and model iteration.
  3. Lead large-scale historical backfills and migration initiatives to ensure data consistency and integrity across evolving storage and compute platforms.
  4. Optimize data workflows through advanced query tuning, indexing, partitioning, and cost optimization strategies to support efficient large-scale analytics.
  5. Architect and maintain high-performance cloud-based data platforms using modern data stack components across AWS, GCP, or Azure.

Skills

Required

  • 5+ years of experience in software engineering, with 2+ years focused on data engineering, building and operating large-scale data platforms.
  • Proven experience designing and optimizing data pipelines, data warehouses, and big data solutions.
  • Strong proficiency in data and advanced SQL, including: Complex analytical queries, Query performance tuning, Indexing & partitioning strategies
  • Experience working with Relational and NoSQL databases
  • Large-scale queue systems (Kafka, SQS, etc.)
  • Experience working with Distributed processing engines
  • Strong background in distributed systems and event-driven architectures.
  • Experience working with cloud-native infrastructure and high-scale systems.
  • Practical experience deploying and operating services in Kubernetes-based environments.

Nice to have

  • Experience with additional data processing frameworks beyond the core stack.
  • Background in cybersecurity-related data infrastructure projects.
  • Familiarity with advanced machine learning workflows and their unique data challenges.
  • Contributions to open-source data engineering tools or frameworks.
  • Data lakes and modern storage formats (Delta Lake, Iceberg, Snowflake)

What the JD emphasized

  • large-scale data platforms
  • large-scale historical backfills
  • large-scale analytics
  • high-scale systems
  • large-scale queue systems
  • massive volumes of structured and unstructured data
  • large-scale queue systems

Other signals

  • data infrastructure
  • data pipelines
  • data warehouses
  • model training
  • model inference