About Kape Technologies Kape is a cybersecurity company focused on helping everyone have a better digital experience with greater privacy and protection. With over 1000 experienced individuals across ten global locations, including the UK, Israel, Germany, Romania, France, the Philippines, USA, Singapore, Hong Kong, and Cyprus, the Kape team is guided by a single mission: to create a more secure and safe world. Job Summary If you’re passionate about developing people and building scalable, modern data platforms, this could be the role for you. We’re building a world-class, data-driven organization, and at the core of that mission is a high-performance, cloud-native data platform. This platform empowers embedded analysts and enables engineering teams across the company to make timely, data-informed decisions. As Lead Data Engineer, you’ll lead a team of data and analytics engineers while remaining hands-on with the platform itself. You’ll work with large-scale datasets that power both automated systems and human decision-making, acting as a central connector between data producers and consumers across the organization. Core Responsibilities People Leadership Lead, coach, and mentor a team of data engineers and analytics engineers Manage day-to-day team tasks, priorities, and workload distribution Support career development through regular 1:1s, feedback, and growth plans Remove technical and organizational blockers to help the team succeed Participate in hiring, onboarding, and integration of new employees to build a strong, effective team Technical Leadership Architect, build, and maintain a scalable data platform for ingestion, anonymization, and enrichment of data Deliver high-quality analytical datasets using analytics engineering best practices Define, implement, and champion data engineering best practices and workflows across the team (coding standards, testing, code review, documentation) Partner closely with internal stakeholders to translate business needs into technical solutions Proactively identify risks and resolve dependencies across teams Provide tooling, documentation, and guidance to data consumers across the company Tech Stack Languages & Tools: Python, SQL Data Warehousing & Query Engines: Snowflake, AWS Redshift, Athena Pipeline & Orchestration: Apache Airflow, AWS Glue, dbt Cloud & DevOps: AWS (Lambda, S3, IAM), Docker, Terraform Streaming: Kafka, Kinesis BI & Analytics: Tableau, Power BI Core Requirements 5+ years of experience in data engineering or analytics engineering At least 2 years of experience managing and leading a team (performance reviews, 1:1s, mentoring, career planning, onboarding new team members) Strong hands-on experience with SQL and Python Deep experience designing and maintaining data models in large-scale data warehouses Proven ability to design reliable, testable data pipelines Experience building and operating data systems in cloud environments (AWS preferred) Strong understanding of software engineering best practices, including version control and CI/CD Experience establishing or improving team workflows and engineering standards Excellent communication skills, with the ability to explain technical concepts to diverse audiences Nice to Have Familiarity with BI tools such as Tableau or Power BI Experience with Apache Airflow and dbt Experience using Terraform or other infrastructure-as-code tools Knowledge of data privacy and security principles in production systems #LI-DN 1