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Webentwickler à France

Software Engineer- Data Engineering (Remote from Germany)

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À distance
EUR 75 000 - 95 000
Il y a 6 jours
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Software Engineer- Data Engineering (Remote from Germany)
Jobgether
À distance
EUR 75 000 - 95 000
Plein temps
Il y a 6 jours
Soyez parmi les premiers à postuler

Résumé du poste

A tech recruitment agency is seeking an experienced Software Engineer for Data Engineering in Germany. In this role, you will design and implement high-performance data pipelines while collaborating closely with cross-functional teams. The ideal candidate will have over 7 years of relevant experience, strong skills in Python and SQL, and a passion for solving complex data challenges. You will work in a flexible remote-first environment and mentor other engineers while contributing to a next-generation data platform.

Prestations

Competitive salary with equity participation
Comprehensive health benefits
Unlimited vacation policy
Professional growth opportunities

Qualifications

  • Bachelor’s degree in Computer Science, Data Science, Engineering, or similar.
  • 7+ years of experience in data or software engineering.
  • Advanced programming skills in Python and SQL.

Responsabilités

  • Design, implement, and maintain scalable ETL/ELT pipelines.
  • Build and optimise data models for cloud warehouses.
  • Lead large-scale data initiatives from planning to execution.

Connaissances

Python programming
SQL skills
ETL/ELT pipeline development
Data quality assurance
Distributed systems knowledge
Mentoring skills

Formation

Bachelor's degree in Computer Science

Outils

Postgres
AWS
Airflow
Databricks
Description du poste

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Software Engineer – Data Engineering in Germany.

In this role, you will be a key contributor to the design, development, and scaling of a next‑generation data platform that supports critical business operations and AI initiatives. You will lead the creation of high‑performance data pipelines, cloud‑based architectures, and data models that enable near real‑time analytics and machine learning. Collaborating closely with engineers, data scientists, and product teams, you will ensure data quality, observability, and operational excellence across all systems. This position requires hands‑on technical expertise, a strong understanding of distributed systems, and a passion for solving complex data challenges in a fast‑paced, innovative environment. You will also mentor other engineers and contribute to shaping the long‑term data strategy while working in a collaborative, remote‑first culture.

Accountabilities
  • Design, implement, and maintain scalable ETL/ELT pipelines using Python, SQL, and modern orchestration frameworks.
  • Build and optimise data models and schemas for cloud warehouses and relational databases, supporting AI and analytics workflows.
  • Develop and operate distributed, real‑time data systems for high‑throughput ingestion and processing.
  • Collaborate with cross‑functional teams including AI, engineering, and product to deliver high‑quality datasets and robust data products.
  • Lead large‑scale data initiatives from planning through execution, ensuring performance, cost efficiency, and reliability.
  • Mentor and provide architectural guidance to other engineers, promoting best practices in data engineering and pipeline development.
  • Support testing, debugging, and QA processes to ensure system stability and data integrity.
Requirements
  • Bachelor’s degree in Computer Science, Data Science, Engineering, or a related technical field. Graduate degrees are a plus.
  • 7+ years of progressive experience in data or software engineering, building complex data systems.
  • Advanced programming skills in Python and SQL; experience with orchestration/streaming frameworks such as Temporal, Dagster, Airflow, Spark, or Kafka.
  • Strong knowledge of relational and NoSQL databases (Postgres, MySQL, MongoDB, ElasticSearch, Cassandra).
  • Experience with cloud computing and data warehousing platforms, preferably Databricks and AWS.
  • Familiarity with ML feature stores and productionising ML pipelines is a plus.
  • Strong analytical skills, attention to data quality, and experience with both OLTP and OLAP systems.
  • Experience mentoring engineers and providing technical and architectural guidance.
  • Bonus: experience with energy market or weather data, dbt, DataOps practices, real‑time data technologies, or knowledge of power systems.
Benefits
  • Competitive salary with equity participation and long‑term growth potential.
  • Comprehensive health benefits including medical, dental, and vision coverage.
  • Flexible, remote‑first working environment with unlimited vacation policy.
  • Opportunities for accelerated professional growth and mentorship from industry experts.
  • Collaborative, inclusive culture focused on innovation and impact.
Why Apply Through Jobgether?

We use an AI‑powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role’s core requirements. Our system identifies the top‑fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre‑contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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* Le salaire de référence se base sur les salaires cibles des leaders du marché dans leurs secteurs correspondants. Il vise à servir de guide pour aider les membres Premium à évaluer les postes vacants et contribuer aux négociations salariales. Le salaire de référence n’est pas fourni directement par l’entreprise et peut pourrait être beaucoup plus élevé ou plus bas.

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