Data Engineer, Data Exchange — Copenhagen (Flexible Hours)

Zeta-Global

København

Hybrid

DKK 650,000 - 850,000

Full time

3 days ago
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Benefits offered by this job

Health insurance
Remote work option
Flexible hours
Lunch provided

Job summary

Zeta Global in Copenhagen is seeking a Data Engineer to join the Data Exchange team. You will contribute to analysis, development, and maintenance of our data infrastructure and pipelines.

The role offers autonomy, collaboration with global teams, and exposure to AWS-based tools, Spark, Airflow, and scalable data solutions.

We value curiosity, strong coding skills in Python/Scala, and a proactive approach to solving data challenges.

Qualifications

  • Strong academic background in a quantitative field.
  • Hands-on experience building scalable data pipelines.
  • Proficiency in Python, Scala, or other OOP languages for data engineering and processing tasks.
  • Strong data analysis skills, including working with large datasets.
  • Knowledge of distributed data processing for batch workloads.
  • Solid understanding of database technologies.

Responsibilities

  • Develop, analyze and maintain complex data pipelines.
  • Collaborate with international product stakeholders.
  • Participate in agile development and rapid prototyping.
  • Translate real-world challenges into data models and code.
  • Contribute to data infrastructure and software development.

Skills

Python
Scala
Data analysis
Data pipelines
CI/CD
SQL
OOP
Airflow
Spark
AWS

Education

Quantitative field degree (CS/Math/Physics)

Tools

Airflow
Apache Spark
AWS
S3
Glue
Athena
EMR

Job description

Zeta Global in Copenhagen is seeking a Data Engineer to join the Data Exchange team. You will contribute to analysis, development, and maintenance of our data infrastructure and pipelines.

The role offers autonomy, collaboration with global teams, and exposure to AWS-based tools, Spark, Airflow, and scalable data solutions.

We value curiosity, strong coding skills in Python/Scala, and a proactive approach to solving data challenges.

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