Data Platform Manager

LocalStack

Zürich

Hybrid

GBP 90,000 - 140,000

Full time

7 days ago
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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 - the Local Cloud Sandbox for Developers and AI Agents

We are a fast-growing Series A startup building cutting-edge technology to revolutionize cloud development processes and support highly efficient dev&test feedback loops. We’ve closed our last $25mil round in Q4 2024, led by Notable Capital, CRV and Heavybit.

LocalStack is a local cloud development platform. LocalStack makes it easier, faster, and less expensive for software teams to ship reliable, high-quality applications to the cloud.

The cloud was built to run software, not to support AI-native development workflows. As the world's leading local cloud development platform, LocalStack provides secure local sandboxes that simulate cloud environments, enabling AI agents and software developers to find and fix risks faster and more effectively than they can in the cloud.

Our customer base ranges from SMBs to Global Fortune 500 companies. Our clients include companies like NASA, Harness, IBM, Workday, Comcast, Apple, 3M, Block and many more.

We are sustainably growing our globally distributed teams across GTM, operations and engineering. In 2025 we almost doubled in size and continue to grow across all areas in 2026.

LocalStack is headquartered in Zurich/Switzerland , with a small engineering office in Vienna/Austria and remote team members from 25 countries including the US, FR, UK, CA, ES, and many more!
Check our Notion Candidate Handbook and our GitHub!

What you will be working on/responsible for
  • Build and evolve a self-service data platform that enables Product, Engineering, and GTM teams
  • Define and maintain data quality standards, SLAs/SLOs, monitoring, and incident-response processes. Own GTM-facing data support, manage data access appropriately, and identify and address potential PII exposure.
  • Establish canonical data models, consistent metric definitions, and modelling standards across priority domains.
  • Establish effective planning, delivery processes, documentation, and ways of working, including the use of AI tools.
  • Own quarterly data OKRs and prioritise a balanced roadmap covering business needs and measure success through business impact, and improved efficiency.
  • Directly manage and develop the Data team through regular one-to-ones, feedback, performance management, and hiring.
Experience we expect you to bring to the role
  • Hands-on data experience (6+ years) across data engineering and analytics, comfortable building pipelines
  • Experience with Python, SQL, Snowflake or equivalent, real-time analytics (Tinybird, ClickHouse, or similar), AI-assisted coding tools day to day
  • Experience building reusable datasets, documentation, or a metrics / BI layer that non-data teams adopted and used without help
Values we hold in LocalStack
  • Care: we create with compassion. We prioritize empathy and understanding in every interaction. By genuinely caring for our team, customers, and community, we create an environment where people thrive and impactful work flourishes
  • Ownership: we own the outcome. We take responsibility for our work and are passionate about its impact. We foster autonomy, inspire ambition, encourage ownership, and empower everyone to unlock their potential and make an impact.
  • Openness: we build trust together. We build trust through open communication and honest feedback. By sharing ideas and embracing diverse perspectives, we create stronger, more connected teams that work toward shared goals.
  • Courage: we dare to innovate. We embrace bold challenges and take calculated risks to move the needle. We step outside our comfort zones, experiment fearlessly, and turn setbacks into springboards for growth.
  • Excellence: we chase the extraordinary. We chase excellence by pushing boundaries and delivering results that go beyond the ordinary, constantly raising the bar and striving for greatness in everything we do. Excellence is not just the outcome, itʼs how we approach every task with purpose, passion, and a commitment to delivering exceptional value.
Benefits
  • Fully remote
  • Competitive salary
  • Annual company retreat
  • 2 extra company-wide holidays
  • Friendly and inclusive workplace culture (community guilds and online company events)

Please note, that due to a high volume of candidates, we cannot offer personalized feedback to each candidate.

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