R&D Team Lead – Data Engineering (Security)

About the role

JFrog is looking for an experienced R&D Team Lead to head a group of five Data Engineers focused on large‑scale data ingestion and processing for its security business. The role blends technical leadership with hands‑on architecture design in a fast‑moving, data‑intensive environment.

Key responsibilities

• Lead, mentor and support a team of five engineers, handling task prioritisation, technical guidance and career development.
• Own the technical direction and architecture of critical data pipelines, ensuring scalability, resilience and performance.
• Design solutions for complex, constantly changing internet data sources and large‑volume batch and streaming workloads.
• Collaborate with DevOps, infrastructure, security and product teams to align technical solutions with business needs.
• Drive best practices in code quality, observability, documentation and operational excellence.
• Participate in hands‑on development and technical reviews as required.

Required profile

• Proven experience leading or mentoring engineers on a technical team.
• Strong background with relational and/or NoSQL databases, including schema design and performance optimisation.
• Solid understanding of distributed systems and data‑intensive applications.
• Experience designing and maintaining batch and/or streaming data pipelines.
• Familiarity with Change Data Capture (CDC), ETL mechanisms and large‑scale orchestration systems.
• Knowledge of software package ecosystems, registries and versioning concepts.
• Experience working with internet‑scale data sources or ingestion platforms.
• Hands‑on experience with Python.

Required skills

• Python
• Relational databases (e.g., PostgreSQL, MySQL)
• NoSQL databases (e.g., Cassandra, MongoDB)
• Schema design and performance tuning
• Distributed systems concepts
• Data pipeline development (batch & streaming)
• Change Data Capture (CDC)
• ETL processes
• Orchestration tools (e.g., Airflow, Prefect)
• Software package registries and dependency metadata
• Internet‑scale data ingestion techniques