We are looking for an experienced Team Lead to lead a team of 5 Data Engineers responsible for handling large-scale data from diverse internal sources. This role combines technical leadership with hands-on architectural decision-making in a highly complex and data-intensive domain, which is the critical path for JFrog business. The ideal candidate will guide the team through challenges related to shipping data fast, accurate in streams and batches, aggregating and maintaining internal database sources alongside scale, reliability, and performance, while ensuring high engineering standards and effective collaboration.
As a Data Engineering Team Lead–, you will...
Lead, mentor, and support a team of 5 engineers, including task prioritization, technical guidance, and career development
Own the technical direction and architecture of systems responsible for a large-scale data pipeline in the business’ critical path.
Design and oversee solutions that handle complex and constantly changing internet sources
Ensure systems are scalable, resilient, and efficient when dealing with vast volumes of data
Collaborate with adjacent teams (e.g., devops-data, infrastructure, security, product) 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 needed
To be a Team Leader – Data Crawling & Ingestion, you need…
Proven experience leading or mentoring engineers on a technical team
Strong background in working with databases (relational and/or NoSQL), including schema design and performance considerations
Solid understanding of distributed systems and data-intensive applications
Strong problem-solving skills and ability to operate in a complex, evolving domain
Experience designing or maintaining data pipelines (batch and/or streaming)
Familiarity with CDC strategies, ETL mechanisms, and large-scale multi-job orchestrator systems
Understanding of software package ecosystems and protocols (e.g., package registries, dependency metadata, versioning concepts)
Experience working with internet-scale data sources or ingestion platforms
Familiarity and experience with Python
