Data Engineering Lead (Hands-On)

At JFrog, we’re reinventing DevOps to help the world’s greatest companies innovate – and we want you along for the ride. This is a special place with a unique combination of brilliance, spirit and just all-around great people. Here, if you’re willing to do more, your career can take off. And since software plays a central role in everyone’s lives, you’ll be part of an important mission. Thousands of customers, including the majority of the Fortune 100, trust JFrog to manage, accelerate, and secure their software delivery from code to production – a concept we call “liquid software.” Wouldn't it be amazing if you could join us in our journey?

We are looking for a Data Engineering Lead to join our Platform Group at JFrog. In this role, you will drive the development of scalable data pipelines and infrastructures that are crucial to our platform’s success. You will collaborate across departments, and innovate to ensure our data ecosystem is robust, secure, and optimized for growth.

• Architect and develop data pipelines – Lead the design and implementation of data pipelines that support JFrog's platform, ensuring high data quality, security, and governance. Introduce new tools and technologies to enhance data workflows and integration
• Develop a strategic roadmap that outlines key engineering solutions to support our platform’s scalability and performance, aligned with JFrog's overall vision and objectives
• Collaborate across teams – Work closely with internal teams including DevOps, BI, Product, and development groups to ensure seamless data integration and drive data-driven decision-making across the organization
• Establish data guidelines and documentation – Define best practices for data generation, consumption, and management within the platform. Create thorough documentation for all data processes to facilitate clear communication and future maintenance

• 5+ years hands-on proven experience designing, building, and optimizing scalable and highly available data-intensive systems
• In-depth understanding of big data engines and frameworks, such as Spark, and experience with ETL/ELT tools for robust data pipeline development
• Proven ability to lead initiatives and drive technical agendas in a hands-on capacity, with potential for team building in the future
• Knowledge of machine learning frameworks and strategic industry trends – a plus
• Strong business skills and strategic thinking, an innovative and growth mindset
• Strong interpersonal skills to collaborate with internal teams and external partners effectively