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Senior Data Engineer*

JR Germany

Braunschweig

Vor Ort

EUR 55.000 - 80.000

Vollzeit

Vor 30+ Tagen

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Zusammenfassung

A leading company in the data science field is seeking a Data Engineer to enhance business processes using machine learning and optimization techniques. The role involves designing data architectures, mentoring junior staff, and collaborating in an agile environment. Candidates should have a Master's degree and extensive experience with data technologies. The position offers a secure contract, competitive salary, and numerous benefits.

Leistungen

30 days of vacation
Attractive salary
Further training opportunities
Structured onboarding and mentoring program
30% staff discount at NEW YORKER stores
Company and team events
Canteens with diverse food selection

Qualifikationen

  • Three or more years of working experience as a data engineer or similar position.
  • Good spoken and written German is a plus, fluent English is a must-have.

Aufgaben

  • Design, implement and optimize effective data processing architectures in Python.
  • Mentor more junior team members through insightful code reviews and pair programming sessions.
  • Operationalize machine learning pipelines together with a team of highly motivated data scientists.

Kenntnisse

Data processing architectures
Data quality
Python
Spark
Hadoop
SQL
ETL pipelines
Docker
Kubernetes
Communication

Ausbildung

Master's degree in Computer Science or equivalent

Tools

PySpark
Airflow

Jobbeschreibung

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The Data Science department uses state-of-the-art machine learning and optimization techniques to continuously improve business processes at NEW YORKER. We work in agile project teams on a variety of use cases, including image recognition, order optimization, pricing, distribution and logistics. We are a very ambitious and international team and are proud of our high standards.

  • Design, implement and optimize effective data processing architectures in Python
  • Extract, transform, analyze, clean and model data from different sources
  • Implement and operate maintainable and reliable data pipelines using PySpark and Airflow with a strong focus on data quality
  • Strive to understand how the data is actually generated and what impact this has on data quality and our use cases through proactive communication with other departments
  • Operationalize machine learning pipelines together with a team of highly motivated data scientists
  • Architect and develop continuous integration & deployment processes
  • Operate and optimize Hadoop (Cloudera) clusters with support of the DevOps and Infrastructure teams
  • Mentor more junior team members through insightful code reviews and pair programming sessions
  • Master's degree in Computer Science or equivalent
    Three or more years of working experience as a data engineer or similar position
  • Extensive experience with Spark, Hadoop, SQL & relational databases, data models and ETL pipelines
  • Ability to write efficient, well-tested code with a keen eye on scalability and maintainability in Python; Airflow and Scala experience is a plus
  • Experience with Docker, Kubernetes and usage of continuous integration & deployment is a plus
  • You are a team player and strong communicator with a hands-on mentality
  • Good spoken and written German is a plus, fluent English is a must-have
  • A secure, permanent job in an internationally operating company in a future-proof industry that is characterized by growth
  • Participation in shaping the digital transformation in an innovative company
  • Permanent employment contract with 30 days of vacation, an attractive salary and further training opportunities/career model
  • A structured onboarding and mentoring program in a great team with international colleagues, a “Duz Kultur” and open doors
  • Numerous benefits, such as a 30% staff discount at our NEW YORKER stores, company and team events, and canteens with a diverse food selection

*Your gender doesn't matter to us - the main thing is that you fit in with us! NEW YORKER is open to all people who want to contribute to our company's success.

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