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Data Engineer

Quicklizard

Where
Petah Tikva, Israel, hybrid
Language, from the listing
No Hebrew mentionedA missing mention doesn't mean Hebrew isn't needed. Ask if it matters to you.
Dates
Found 13 Oct 2026
Last checked on the employer's site
1 h ago (13 Oct 2026)
Source
Employer career page (Comeet)

What they ask for

  • 5+ years in data engineering, with real production experience at scale (terabytes+, billions of rows)
  • Deep SQL and strong distributed-processing experience (Spark or equivalent)
  • Strong Python and/or Go
  • Hands-on experience with cloud data warehouses (BigQuery, Snowflake, Redshift) and orchestration tooling
  • AI-first mindset - you actively work with AI coding tools (Claude Code, Cursor, Copilot) and LLM-based agents as part of your day-to-day, and look for opportunities to automate and accelerate engineering work with them
  • Experience building or supporting AI/LLM-driven data products - pipelines that feed models, agents, or ML systems
  • Product mindset: you care why the data is being used, not just that the job finished green

Nice to have

  • Nice to have: streaming architectures, cost/FinOps ownership, multi-region or multi-cloud systems, e-commerce or pricing domain experience, MCP servers or agentic tooling.

The full listing

Description About Quicklizard Quicklizard is a dynamic pricing platform used by leading retailers, marketplaces, and e-commerce brands worldwide. Our engine ingests sales, competitor, inventory, and cost data and turns it into real-time pricing recommendations - processing billions of records a day across multi-region pipelines that never stop running. The Role We're looking for a Data Engineer to own our data architecture end-to-end. You'll design, build, and scale the pipelines that power every pricing decision we make - from raw ingestion through our data lake to the analytics and BI layers our customers rely on. This is a hands-on leadership role: you'll set technical direction, drive architectural decisions, and mentor a team of data engineers, while still writing code and owning delivery. What You'll Do • Architect and build large-scale batch and streaming ETL/ELT pipelines • Own data lake design, table modeling, and partitioning strategy across billion-row datasets • Drive query performance and cloud cost optimization across AWS and GCP • Establish data quality, observability, and reliability standards - freshness, correctness, and SLAs • Partner with backend, product, and data science teams to expose data through internal and customer-facing APIs Our Stack Spark / EMR · Airflow · BigQuery · PostgreSQL & Aurora · Kafka · RabbitMQ · Elasticsearch · Go · Python · AWS · GCP · Kubernetes · Terraform What We're Looking For • 5+ years in data engineering, with real production experience at scale (terabytes+, billions of rows) • Deep SQL and strong distributed-processing experience (Spark or equivalent) • Strong Python and/or Go • Hands-on experience with cloud data warehouses (BigQuery, Snowflake, Redshift) and orchestration tooling • AI-first mindset - you actively work with AI coding tools (Claude Code, Cursor, Copilot) and LLM-based agents as part of your day-to-day, and look for opportunities to automate and accelerate engineering work with them • Experience building or supporting AI/LLM-driven data products - pipelines that feed models, agents, or ML systems • Product mindset: you care why the data is being used, not just that the job finished green Nice to have: streaming architectures, cost/FinOps ownership, multi-region or multi-cloud systems, e-commerce or pricing domain experience, MCP servers or agentic tooling.