Data Analytics Engineer

Data Analytics Engineer

Berlin Vollzeit 60000 - 80000 € / Jahr (geschätzt) Kein Homeoffice möglich
Doodle

Auf einen Blick

  • Aufgaben: Entwickle skalierbare Datenmodelle und sorge für zuverlässige Analysen.
  • Unternehmen: Doodle, eine innovative B2B SaaS-Plattform mit Millionen von Nutzern.
  • Vorteile: Flexibles Arbeiten, wettbewerbsfähiges Gehalt und ein unterstützendes Team.
  • Weitere Informationen: Dynamisches Umfeld mit großartigen Entwicklungsmöglichkeiten.
  • Warum dieser Job: Gestalte die Datenbasis, die wichtige Produktentscheidungen beeinflusst.
  • Qualifikationen: Erfahrung in der Datenmodellierung und starke SQL-Kenntnisse.

Das prognostizierte Gehalt liegt zwischen 60000 - 80000 € pro Jahr.

Analytics Engineer

Build the Data Foundation That Powers Every Product Decision.

Doodle is a B2B Saa S platform used by millions of professionals to coordinate meetings and collaboration.

As we continue expanding our platform, trusted data has become one of our most valuable products.

Every product decision, customer insight, experiment, and business metric depends on reliable, well‑modelled data.

What You Will Do

As an Analytics Engineer, you will own the analytics platform that enables self‑service insights across Doodle.

  • Analytics Platform
  • Design, build, and maintain scalable analytics data models using dbt and modern data engineering practices.
  • Develop reliable transformation pipelines that convert raw product data into trusted, business‑ready datasets.
  • Own the performance, reliability, and continuous improvement of Doodle's analytics platform.
  • Data Modelling & Semantic Layer
  • Define, document, and maintain trusted business metrics used across the company.
  • Build and evolve a scalable semantic layer that enables consistent reporting and self‑service analytics.
  • Ensure data definitions remain accurate, accessible, and aligned across teams.
  • Data Quality & Governance
  • Own data quality, validation, testing, monitoring, and governance across the analytics stack.
  • Implement best practices for documentation, version control, CI, and automated testing.
  • Establish standards that improve data reliability, consistency, security, and trust.
  • Product Analytics & Experimentation
  • Partner with Product Managers and Analysts to enable experimentation, funnel analysis, retention analysis, and customer insights.
  • Support product launches by providing reliable measurement frameworks and trusted analytics.
  • Enable accurate A/B testing through high‑quality event modelling and instrumentation.
  • Cross‑Functional Collaboration
  • Work closely with Product, Engineering, Data, Marketing, Finance, and Leadership teams.
  • Translate business questions into scalable data models, trusted metrics, and actionable insights.
  • Advise teams on analytics architecture, data modelling standards, and best practices.
  • Influence product and business decisions by making data reliable, accessible, and easy to use.
  • Our Ideal Candidate

We are looking for an Analytics Engineer who combines strong engineering fundamentals with a product mindset and a passion for building trusted, scalable analytics platforms.

  • Analytics Engineering
  • Strong experience building analytics data models using dbt or similar transformation frameworks.
  • Experience orchestrating modern data pipelines using Airflow or similar workflow tools.
  • Advanced SQL skills with experience working on large analytical datasets.
  • Experience working with cloud data warehouses such as Amazon Redshift. Experience with Athena or Spark is an advantage.
  • Programming & Analytics
  • Strong Python skills for data processing and automation.
  • Good understanding of dimensional data modelling, database design, and analytics engineering principles.
  • Familiarity with experimentation frameworks and product analytics.
  • Engineering Excellence
  • Quality first mindset with experience in testing, documentation, version control, and CI.
  • Passion for building reliable, scalable, and maintainable analytics platforms.
  • Strong problem‑solving skills with excellent attention to detail.
  • Collaboration & Communication
  • Excellent communication skills with the ability to explain technical concepts to both technical and non‑technical stakeholders.
  • Comfortable working across Engineering, Product, Analytics, and business teams.
  • Enjoy collaborating in a fast moving Saa S environment.
  • Nice to Have
  • Experience with pandas or similar Python data processing libraries.
  • Experience supporting Product‑Led Growth organizations.
  • Experience building semantic layers or self‑service analytics platforms.
  • Experience with product analytics tools such as Amplitude, Mixpanel, or GA4.
  • Experience working in a modern B2B Saa S environment.
  • Hiring Journey
  • Initial Application Review + BRYQ Assessment
  • Hiring Manager Interview
  • Technical Assessment
  • Cross Functional Technical Interview
  • Executive Interview + HR Interview

So, Get in Touch!

At Doodle, we are committed to providing an environment of mutual trust and respect, where equal employment opportunities are available to all applicants and teammates without regard to age, race, color, disability, religion, gender, or sexual orientation.

Diversity and inclusion are important to us because the best products are built by teams with different experiences, perspectives, and backgrounds.

IMPORTANT NOTICE

Please note that we can only consider your application if you are based and have the right to work in Germany or London.

At this time, we are unable to sponsor visas for this position or support relocation.

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Data Analytics Engineer Arbeitgeber: Doodle

Doodle ist ein hervorragender Arbeitgeber, der eine dynamische und inklusive Arbeitsumgebung bietet, in der Mitarbeiter ihre Fähigkeiten im Bereich Produktwachstum voll entfalten können. Mit einem flexiblen hybriden Arbeitsmodell, großzügigen Urlaubstagen und einem klaren Fokus auf berufliche Weiterentwicklung durch Schulungsbudgets und Konferenzen, fördert Doodle nicht nur das persönliche Wachstum, sondern auch die Teamkultur durch regelmäßige Unternehmensveranstaltungen und gemeinsame Mittagessen. Die Möglichkeit, bis zu drei Monate innerhalb der EU und einen Monat außerhalb der EU zu arbeiten, macht Doodle zu einem attraktiven Arbeitsplatz für Fachkräfte, die nach einer sinnvollen und bereichernden Karriere suchen.

Doodle

Kontaktdaten:

Doodle Recruiting-Team

Wir glauben, dass du diese Fähigkeiten brauchst, um Data Analytics Engineer mit Bravour zu bestehen

dbt
Airflow
SQL
Amazon Redshift
Python
dimensional data modelling
data processing