TL;DR

Senior Data Engineer (Data Science/ML): Build and own critical components of a data platform delivering reliable, scalable data solutions with an accent on data pipelines, semantic modeling, and automated insight delivery. Focus on designing reusable tools, solving complex data challenges, and enabling faster, better data-driven decisions.

Location: Berlin, Germany with hybrid work policy and global presence

Company

%hirify_global% is a global hyperscale scale-up pushing boundaries in open-source technology and multi-cloud data platforms, leveraging popular open-source tools like Apache Kafka and PostgreSQL.

What you will do

Own and deliver key data projects collaborating with Product, Sales, Marketing, and Finance stakeholders.
Design, implement, and maintain data pipelines and modeling solutions.
Build reliable, reusable systems designed for long-term clarity.
Contribute to architectural decisions and advocate best practices in Python, dbt, BigQuery, and modern data tooling.
Mentor peers through clean code, thoughtful reviews, and system design.

Requirements

Location: Based in or able to work in Berlin, Germany
Proven track record delivering complex, large-scale data projects from design to production.
Strong skills in Python, SQL, dbt, and Airflow.
Ability to break down complex business requirements into actionable technical plans.
Focus on building simple, resilient, and lasting data systems.
Collaborative mindset and willingness to share knowledge.

Nice to have

Experience with semantic modeling and automated insight delivery.
Familiarity with BigQuery and modern data tooling.

Culture & Benefits

Equity participation and global hybrid work policy.
Learning budget and support for professional growth.
Global Employee Assistance Program for wellbeing.
Paid open source contribution time and volunteer days.
Health and fitness benefits including massage and Urban Sport Club membership.
Monthly team breakfasts and referral bonus program.

Hiring process

Initial call with Talent Partner (30-45 minutes).
Depth of Expertise interview with hiring manager (45 minutes).
Skills interview or presentation with wider team (1 hour).
Company values interview (1 hour).