Data Engineer Team Lead

A publicly traded, global Consumer Tech company that develops an advanced AI platform leveraging machine learning, computer vision, and predictive analytics to drive highly personalized, direct-to-consumer (D2C) product experiences.

The company utilizes deep technological research to build data-backed, high-scale global brands, combining the stability and compliance of a public enterprise with the fast-paced innovation of a product startup.

Located in the Tel Aviv area with excellent public transit and train accessibility, operating on a hybrid work model (including WFH options).

Position Overview-

• Data Engineering Team Lead / Hands-on Lead managing a distributed squad of 5 engineers (2 based locally, 3 offshore in Ukraine).
• Balancing high-impact, hands-on architecture, pipeline development, and data modeling with team mentorship, code reviews, and task coordination.
• Designing, building, and optimizing scalable ETL/ELT pipelines to ingest, clean, and process massive volumes of unstructured and structured consumer data.
• Architecting cloud-native data layers and infrastructure to support advanced analytics, machine learning workflows, and cross-functional business intelligence.
• Core Domain & Ecosystem- Data Engineering, Distributed Data Pipelines (ETL/ELT), Cloud Infrastructure (AWS), Relational & Non-Relational Big Data Databases, High-Scale SQL & Python, BI Infrastructures (Looker), Distributed Team Management, Agile (Jira).

Requirements-

• 3+ years of professional experience as a Data Engineer building data-intensive infrastructure and processing architectures – Mandatory
• Prior experience or strong capability to lead and mentor engineers within a distributed/hybrid or offshore team structure – Mandatory
• High-level production mastery of Python and SQL for complex data manipulation and pipeline optimization – Mandatory
• Proven hands-on experience designing and deploying automated ETL / ELT workflows – Mandatory
• Solid technical proficiency working within a cloud-native ecosystem, specifically AWS – Mandatory
• Extensive practical background handling large-scale data repositories and complex database environments – Mandatory
• Familiarity or working exposure to BI and data visualization tools (strong preference for Looker) – Advantage
• Experience working within an Agile environment utilizing collaboration tools like Jira – Mandatory