Data Engineer Tech Lead
Company: Quicklizard
Role summary
Data Engineer Tech Lead is a role at Quicklizard in Petah Tikva, Center District, Israel (on-site). Posted 2026-09-06. Experience level: 5-10.
- Job title
- Data Engineer Tech Lead
- Company
- Quicklizard
- Location
- Petah Tikva, Center District, Israel
- Work arrangement
- on-site
- Category
- Data Science
- Experience level
- 5-10
- Date posted
- 2026-09-06
This is a fantastic opportunity to lead a team and shape data solutions at a growing company. You'll have significant autonomy to drive projects and mentor junior engineers, with a competitive salary and benefits package. It's a great chance to make a real impact without needing a formal degree.
Job 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 Engineering Tech Lead 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
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