Data Engineering Team Lead, AI-Driven Platform

lgtcp; Zürich; Hybrid; CHF 180.000 - 240.000; Vollzeit

Benefits dieser Stelle

Home office allowance

Training opportunities

Language skills development

Zusammenfassung

LGT Capital Partners is seeking an experienced team leader to grow a high-performing data engineering team and own the delivery of an enterprise data platform. You will guide technical direction across transactional and analytical architectures and ensure adoption across the organization.

You will collaborate with platform management and other engineering disciplines to embed AI-driven capabilities, improve observability, and drive governance across data pipelines.

Qualifikationen

• 5+ years leading engineering teams, including hiring, coaching, and performance development.
• Production-scale platforms management with reliability and efficiency focus.
• Hands-on with hybrid architectures: transactional/operational and analytical.
• Strong English communication; German a plus.

Aufgaben

• Build, lead and grow a high-performing data engineering team, balancing hands-on work with leadership.
• Own IT delivery of data engineering initiatives across a large-scale landscape.
• Partner with software, integration and AI teams to shape data platform direction.
• Drive AI adoption within data engineering, from tooling to pipelines.
• Ensure operational excellence: reliability, cost-effectiveness, and observability.
• Collaborate with IT and platform management to implement data quality and governance.

Kenntnisse

Team leadership

Large-scale delivery

Hybrid architectures

Azure

Snowflake

dbt

Python

CI/CD

Data platforms

English communication

Tools

Azure

Snowflake

dbt

Python

Jobbeschreibung

LGT Capital Partners is seeking an experienced team leader to grow a high-performing data engineering team and own the delivery of an enterprise data platform. You will guide technical direction across transactional and analytical architectures and ensure adoption across the organization.

You will collaborate with platform management and other engineering disciplines to embed AI-driven capabilities, improve observability, and drive governance across data pipelines.