Data Engineering Team Lead

Why Join Us?

The Checkpoint XPR (Extended Prevention and Response) team is dedicated to constructing the next-generation XDR SaaS platform. XPR offers a unified interface covering Incident Management, Threat Hunting & Asset Management, as well as product management, Workflow Automation, and Automated Prevention.

The XPR Analytics group is actively seeking a dynamic and skilled Team Lead to join our leadership team in a startup-like environment and contribute to shaping, leading, and delivering our innovative cybersecurity solution.

The Analytics Cloud Platform team is responsible for building a scalable and reliable data analytics solution in the cloud. This solution aims to transform diverse security detection data points into a coherent and concise attack picture and response procedure.

Key Responsibilities

• Lead a team of 4-6 proficient software engineers.
• Establish, nurture, and sustain a team of software engineers.
• Provide team leadership through coaching and mentorship.
• Offer technical leadership by guiding solution design and implementation.
• Lead the design and implementation of reliable, scalable, and performant analytical data pipelines making use of modern toolsets and managed services.
• Work closely with our team of data scientists and analysts, who are responsible for developing algorithms, analytical rules, and machine learning data models. Guide your team in the implementation and deployment of these solutions to our cloud platform.
• Work collaboratively with fellow managers and teams to successfully deliver value to our customers.

Qualifications

• BSc in Computer Science or equivalent.
• 5+ years of team leadership experience leading development teams.
• 5+ years of experience in building cloud-based services (Serverless, Blob Storage, S3, Container Apps, E/AKS, Mongo) using event-driven and/or microservice architecture.
• 5+ years of experience in building data engineering solutions.
• 2+ years in cybersecurity solution development.
• Experience creating and optimizing big data processes, pipelines, and architectures on cloud-native environments (Databricks, Synapse, EMR, ADX, HDInsight).
• Experience with big data solutions (Redis, Impala, Presto, Hive, Spark, Flink, Hadoop)
• Proficiency with SQL, Python, and one of Java/Scala/CPP.