At Circus (Xetra: CA1), headquartered in Munich with offices in Berlin and Hamburg, we are pioneering global developments in on-demand autonomous food production. From culinary creation to production and operations, everything is powered by seamlessly integrated robotics and transformative AI.
Our foundation lies in groundbreaking advancements in robotics, driven by artificial intelligence — the long‑missing link in realizing fully autonomous food automation. The time has come for a new status quo: just as autonomous vehicles are reshaping our cities and daily lives, we are redefining the entire experience of food.
Our team brings together leading minds in Robotics, AI, Engineering, and Culinary, working closely with industry‑leading partners to revolutionize how food is prepared, accessed, and experienced.
Join us as we shape a future where the art of cooking meets the science of technology – and where food becomes something fundamentally new.
We are looking for a highly skilled Senior Analytics Engineer to join our team and take ownership of our end‑to‑end analytics infrastructure. In this role, you will architect, implement, and maintain our data models, pipelines, warehouse, and reporting layers. You’ll be the driving force behind turning raw data into actionable insights for business and product teams, enabling data‑driven decisions at all levels of the company.
This is a hands‑on role with high ownership and visibility. You’ll collaborate closely with Engineering, Product, and Operations teams to build a best‑in‑class analytics ecosystem.
Own and manage our analytics infrastructure end‑to‑end: from data ingestion and transformation to reporting and visualization.
Design, develop, and maintain robust data models using DBT and SQL, ensuring high data integrity and performance.
Build and manage data pipelines for batch and real‑time data using Snowflake, DBT, and other relevant tools.
Develop, maintain, and optimize our Google Looker reporting layer to enable self‑serve analytics across the company.
Collaborate with business stakeholders to define KPIs, dashboards, and reporting needs.
Maintain documentation and ensure high‑quality governance practices around data access and lineage.
Drive improvements to analytics processes, automation, and scalability.
Monitor pipeline health, job failures, and data freshness to ensure reliability.
Own and continuously improve our demand forecasting model.
Proven expertise with SQL, DBT, Snowflake, and Google Looker (or similar dashboarding tools).
Strong understanding of modern data stack best practices and dimensional data modeling (e.g., star/snowflake schemas).
Experience working in a production environment with CI/CD pipelines for analytics.
Demonstrated ownership mindset with experience driving analytics projects end‑to‑end.
Excellent communication skills and the ability to translate business needs into technical requirements.
Experience with Python for scripting, data validation, and lightweight data engineering tasks.
Familiarity with the AWS ecosystem, especially Airflow for orchestrating data workflows.
Experience working with event‑driven data architectures.
Ability to troubleshoot complex data issues across different layers of the stack.
Exposure to or experience with time series forecasting and building forecasting pipelines.
Experience designing data engineering pipelines using Python.
Typ:
VollzeitArbeitsmodell:
Vor OrtKategorie:
Erfahrung:
2+ yearsArbeitsverhältnis:
AngestelltVeröffentlichungsdatum:
04 Nov 2025Standort:
WorkFromHome
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