Data Platform Lead - Self-Serve Analytics & Quality

LocalStack; Zürich; Hybrid; GBP 90,000 - 140,000; Full time

Benefits offered by this job

Fully remote

Competitive salary

Annual company retreat

2 extra company-wide holidays

Friendly and inclusive workplace

Job summary

LocalStack is hiring for a senior Data Platform leader to build and scale a self-service data platform that powers Product, Engineering and GTM teams. You will define data quality standards, SLAs, monitoring, and incident response, while ensuring secure data access and addressing potential PII exposure.

You will establish canonical data models, modelling standards, and a BI layer used by non-data teams, driving measurable business impact and efficiency across a 글로벌 team.

Qualifications

• 6+ years of hands-on data experience spanning engineering and analytics.
• Proficiency in Python, SQL, and Snowflake; experience with real-time analytics.
• Experience building reusable datasets and a BI layer adopted by non-data teams.

Responsibilities

• Build and evolve a self-service data platform for Product, Engineering, and GTM teams.
• Define and maintain data quality standards, SLAs/SLOs, monitoring, and incident-response processes; manage GTM data access and address potential PII exposure.
• Establish canonical data models, metric definitions, and modelling standards across priority domains.
• Plan and deliver with documentation and AI tooling; establish effective ways of working.
• Own quarterly data OKRs and prioritize a balanced roadmap tied to business impact and efficiency.
• Directly manage and develop the Data team through regular 1:1s, feedback, performance reviews, and hiring.

Skills

Data pipelines

Real-time analytics

Python

SQL

Tools

Snowflake

Tinybird

ClickHouse

AI-assisted coding tools

Job description

LocalStack is hiring for a senior Data Platform leader to build and scale a self-service data platform that powers Product, Engineering and GTM teams. You will define data quality standards, SLAs, monitoring, and incident response, while ensuring secure data access and addressing potential PII exposure.

You will establish canonical data models, modelling standards, and a BI layer used by non-data teams, driving measurable business impact and efficiency across a 글로벌 team.