Global Head of Data Engineering

About Kape Technologies

Kape is a cybersecurity company focused on helping everyone have a better digital experience with greater privacy and protection. With over 1,000 experienced individuals across ten global locations, the Kape team is guided by a single mission: to create a more secure and safe world.

The Role

If you want to lead data engineering for a global, AI-first company, this is a rare opportunity. Kape is behind ExpressVPN and other privacy brands, and our data platform is at the core of how the company works, serving analysts, engineering teams, leadership and a growing set of AI tools.

As Global Head of Data Engineering, you'll start hands-on, then build and lead a team across several countries, with a real say in where the platform goes next. You will:

• Write SQL, Python and pipelines yourself in your first months

• Lead, coach and grow a team of data engineers across several countries

• Set team priorities and plan delivery, and own hiring and onboarding

• Own the platform's architecture for ingestion, anonymization and enrichment of data, and decide what we keep, change or replace

• Set up a single source of truth: shared metric definitions, building on our semantic layer, that dashboards and AI tools both use

• Set the engineering standards: testing, code review, CI/CD, documentation and alerting

• Partner with finance, marketing, product and engineering to turn business needs into data solutions

Our stack today: Python, SQL, Snowflake, Redshift, BigQuery, Airflow, dbt, AWS, Kafka, Terraform, Tableau and Streamlit. You decide what stays.

What We're Looking For

• 8+ years in data engineering or analytics engineering, including 3+ years leading a team

• You have led a data platform migration or rebuild end to end, with live dashboards and users depending on it

• Strong hands-on SQL and Python, and you still write code

• Deep experience with data modeling, reliable pipelines (Airflow, dbt or similar) and cloud warehouses, ideally on AWS

• You use AI tools daily and know where not to trust them

• Clear communication with engineers and non-technical leaders alike

Bonus: semantic layers or data contracts, subscription-business data (renewals, churn, LTV), Terraform, and data privacy in production systems.