דרושים Data Team Lead בתל אביב

Edikted is a trend-driven global Gen-Z fashion brand that brings pop-culture vibes and must-have styles straight to your closet.

We’re looking for a Data Team Lead to lead and scale our data engineering team, own our data platform end-to-end, and partner with cross-functional teams to drive innovation and business growth through data. This role combines leadership and technical depth - perfect for someone who enjoys managing people while remaining deeply involved in engineering execution.

Responsibilities:

• Lead and mentor the data engineering team, setting goals, providing guidance, and fostering growth.
• Design and maintain scalable data architecture across ingestion, warehousing, modeling, and governance.
• Collaborate with Product, Analytics, and Engineering teams to deliver data solutions that power key business decisions.
• Partner with the VP Analytics to shape and optimize our BI and analytics infrastructure.
• Stay hands-on: build and review pipelines, ensure data quality, and improve system performance.
• Establish and uphold best practices in testing, CI/CD, documentation, and data governance.
• Define team roadmaps, set priorities, and communicate effectively with all stakeholders.

Requirements:

• 6+ years of experience in data engineering, including at least 2 years in a leadership or team lead role.
• Proven experience designing and maintaining modern cloud-based data architectures (batch and streaming).
• Strong SQL and Python skills with deep understanding of data modeling and transformation frameworks.
• Hands-on experience with orchestration tools (e.g., Airflow, Prefect) and dbt.
• Experience working with major data warehouses (BigQuery, Snowflake, Redshift, or Databricks).
• Familiarity with data quality and observability tools (e.g., dbt tests, Great Expectations, Soda).
• Excellent communication and leadership skills, with the ability to drive both strategy and execution.

Nice to Have:

• Experience in eCommerce or consumer data environments.
• Knowledge of event streaming and customer data tools (Kafka, Segment, GA4).
• Exposure to experimentation platforms or ML feature stores.
• Understanding of data privacy and governance (GDPR, RBAC, data retention).