Senior Data Analytics Engineer
Listed on 2026-03-06
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IT/Tech
Data Analyst, Data Engineer
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.
At its core, Local Stack provides a high-fidelity emulator and local cloud development platform. Imagine developing cloud applications and data pipelines entirely on your local machine within a lightweight cloud sandbox, running in Docker!
Our mission is to empower developers to rapidly build and test their cloud applications, allowing for a more enjoyable dev experience, and saving valuable time and resources.
Local Stack has a large and active open-source community (57k+ stars on Git Hub) with over 100k active users worldwide and 290M+ downloads to date. Our customer base ranges from SMBs to Global Fortune 500 companies.
We are sustainably growing our globally distributed team across sectors.
Local Stack is headquartered in Zurich/Switzerland 🇨🇭, with a main engineering office in Vienna/Austria 🇦🇹 and remote team members from 🇺🇸the US, 🇫🇷FR, 🇬🇧UK, 🇨🇦CA, 🇪🇸ES, and many more countries.
👉Check our Notion Candidate Handbook and our Git Hub!
This is the right opportunity for a person with 5+ Years experience in a Data Analytics role designing, building, and maintaining the core data models that power critical business decisions.
Requirements- Deliver a coherent, trusted semantic layer for the business by creating a core set of reusable, well-documented data models (dimensions, facts, and metrics) that become the single source of truth for priority domains such as product usage, customer journey, billing, activation, and performance.
- Drive adoption of these canonical models so that 80%+ of downstream dashboards and analyses rely on them.
- Translate ambiguous, evolving business logic into clear, unambiguous data specifications, producing high-quality requirements and modelling documentation used by engineering, finance, and product teams.
- Improve data reliability and model quality by implementing robust testing, lineage, and auditability across all new models, and systematically refactoring legacy models to remove duplication, ambiguity, and performance bottlenecks.
- Enable self-serve insights by designing intuitive data models and documentation that allow product managers and GTM teams to answer most analytical questions independently.
- Establish and standardise modelling conventions, naming standards, and metric definitions across the organisation to ensure consistent interpretation of data.
- Drive cross-functional alignment on KPIs and business logic, preventing metric drift and leading discussions that bring clarity to ambiguous or sensitive metrics.
- Deep experience with data modelling (dimensional, semantic, entity-relationship, metric-layer design)
- Proven skill transforming business domain knowledge into structured schemas
- Mastery of SQL and transformation frameworks
- Experience with data warehouse performance optimisation techniques, including materialisation strategies and cost-aware choices
- Strong data quality, testing, and lineage awareness
- Experience working directly with business partners (Product, GTM, Finance) to understand and codify KPIs
- Experience with Tinybird, Click House, or real-time warehouses
- Experience implementing metric layers or headless BI
- Prior work in a fast-paced Series A or early-stage startup
- Familiarity with schema registries, governance frameworks, and semantic modelling tools
- 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…
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