Data Engineer

vor 1 Monat

Berlin, Deutschland Cititec Talent Vollzeit
Einleitung

Data Engineer | €90-110,000 | Berlin | Permanent


Industry: eCommerce

Location: Berlin - Hybrid onsite

Job type: Permanent

Salary: €90-110,000


The Role

Cititec Talent has partnered with a leading eCommerce company looking to bring a Data Engineer

into the team. As a Data Engineer within the Markets Machine Learning Engineering team, your

responsibilities encompass designing, developing, and managing data and machine learning pipelines essential for driving high-value production machine learning systems across demand and supply channels.

Key business areas rely on the data delivered by your team. Continually pushing boundaries, you and your team provide high-performance data processing solutions that prioritize efficiency, reliability, and scalability, challenging conventional approaches.


What you’ll do

  • Build, and manage dependable data integration pipelines handling large data volumes to deliver high-quality data products.
  • Work closely with our product managers, data scientists, and fellow data engineers to innovate and test new ideas and pipelines.
  • Utilise and enhance a cloud-based (AWS) technology stack comprising Databricks Spark, Airflow, and Python.
  • Influence our engineering culture positively by fostering knowledge exchange and spearheading technical discussions and innovations within our engineering community.


Requirements

  • Strong background in software or data engineering with a comprehensive understanding of data structures and algorithms.
  • Proficiency in implementing ETL pipelines using cutting-edge technology stacks (such as Databricks, Spark, Airflow, AWS - experience with SageMaker is advantageous) and distributed data platforms.
  • Analytical mindset and robust coding abilities in Python and SQL, emphasising the creation of clean, readable, and maintainable code.
  • Understanding of SQL, ETL design, data and interface specifications, quality assurance, and testing methodologies.
  • Familiarity with cloud-based technologies for application development, including Kubernetes and Docker.
  • Knowledge of data modeling techniques for Business Intelligence systems, including the Star Schema methodology.

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