ExpressVPN

Global Head of Data Engineering

ExpressVPN Tel-Aviv, Tel-Aviv District, Israel

Software Development · 201-500 employees

22 h ago
Principal (10+ yrs) Full-time Israel
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About the role

You will lead, coach, and grow a global team of data engineers while setting engineering standards and priorities. Additionally, you will own the platform's architecture for data ingestion, enrichment, and the creation of a single source of truth for metrics.

What they look for

Data Engineering SQL Python Snowflake Redshift BigQuery Airflow Dbt AWS Kafka Terraform Tableau Streamlit Data Modeling Team Leadership Data Architecture

Requirements

The role requires 8+ years of experience in data or analytics engineering with at least 3 years in a leadership capacity. Candidates must possess strong hands-on skills in SQL, Python, and cloud-based data warehousing, along with experience in managing end-to-end platform migrations.

Full description

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.