Data Engineering Team Lead
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 a Data Engineering Team Lead, 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
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