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.
Skills Required
- 5+ years of data engineering experience
- Production experience processing terabytes of data and billions of rows
- Deep SQL expertise
- Strong distributed-processing experience with Spark or equivalent
- Strong Python and/or Go skills
- Hands-on experience with cloud data warehouses such as BigQuery, Snowflake, or Redshift
- Experience with orchestration tooling
- Experience using AI coding tools and LLM-based agents in daily engineering work
- Experience building or supporting AI/LLM-driven data products
- Proven technical leadership, including mentoring and architectural ownership
- Product mindset focused on how data is used
- Streaming architecture experience
- Cost or FinOps ownership
- Multi-region or multi-cloud systems experience
- E-commerce or pricing domain experience
- MCP servers or agentic tooling experience
What We Do
Quicklizard offers an ML- and AI-powered dynamic pricing platform for retailers and brands. Its software helps companies streamline and optimize pricing across product catalogs, channels, and markets, automating pricing decisions and supporting more confident, responsive retail strategies. The company applies machine learning and artificial intelligence to pricing optimization, enabling retailers and direct-to-consumer businesses to manage prices more efficiently and effectively at scale.
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