Data Engineering Lead - AI-Driven Platform & Team Growth

LGT Capital Partners AG; Zürich; Hybrid; CHF 180.000 - 280.000; Vollzeit

Benefits dieser Stelle

Work-from-home options

Flexible hours

Home office allowance

Zusammenfassung

LGT Capital Partners AG in Switzerland is seeking an experienced team leader to grow a high-performing data engineering team and own the delivery of an enterprise data platform across a complex landscape.

You will balance hands-on technical involvement with people leadership, partnering with architecture, product, and business teams to ensure reliable outcomes. You will drive AI-enabled data pipelines and ensure governance and observability across platforms.

Qualifikationen

• Track record delivering large-scale, complex products.
• 5+ years leading engineering teams, including people leadership.
• Production-scale platforms experience, reliability and observability.
• Strong hands-on in hybrid architectures (transactional + analytical).
• Knowledge of Azure, Snowflake, dbt, and Python is advantageous.
• English fluent; German is a plus.

Aufgaben

• Build, lead and grow a high-performing data engineering team.
• Own IT delivery of data engineering initiatives.
• Collaborate with architecture, software, integration and AI teams.
• Drive AI adoption within data engineering.
• Ensure operational excellence and cost efficiency.
• Drive data quality, observability and governance.

Kenntnisse

Leadership

Data engineering

AI adoption

Stakeholder management

Communication

Cloud data platforms

Python

CI/CD

Tools

Azure

Snowflake

dbt

Python

CI/CD

Jobbeschreibung

LGT Capital Partners AG in Switzerland is seeking an experienced team leader to grow a high-performing data engineering team and own the delivery of an enterprise data platform across a complex landscape.

You will balance hands-on technical involvement with people leadership, partnering with architecture, product, and business teams to ensure reliable outcomes. You will drive AI-enabled data pipelines and ensure governance and observability across platforms.