JobCubby JobCubby
Sign up
Quicklizard

Data Engineer

Quicklizard Petah Tikva, Center District, Israel

Technology, Information and Internet · 51-200 employees

4 h ago
data-engineer Senior (5-10 yrs) Full-time Israel
Create a free account to apply — email only, no card. You can also save this posting or score it against your profile with AI.

About the role

You will architect and build large-scale batch and streaming data pipelines while owning the end-to-end data architecture. Additionally, you will lead the technical direction, mentor team members, and ensure data quality and performance across the platform.

What they look for

Data Engineering Spark Python Go SQL BigQuery AWS GCP ETL Data Lake Airflow Kafka Kubernetes Terraform Data Modeling Distributed Systems

Requirements

The role requires over 5 years of experience in data engineering with expertise in distributed processing and cloud data warehouses. Candidates must demonstrate strong proficiency in Python or Go and have a proven track record of technical leadership.

Full 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
  • Lead technically: review designs and code, mentor engineers, and raise the bar for the data org

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
  • Proven technical leadership - mentoring engineers, owning architecture, driving decisions across teams
  • 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.

Requirements

null

Similar roles