Senior Data Engineer (Finance, Copenhagen)

Job summary

The role involves driving data engineering initiatives within the End Of Day Value stream, focusing on delivering high-quality data for reporting purposes. The position is part of a team dedicated to building data and reporting solutions using advanced data engineering technologies.

Qualifications

• Extensive experience in data engineering with a strong understanding of best practices, including automated testing and continuous integration.
• Familiarity with data engineering principles, data pipelines, and the concept of Data Mesh.
• Proficient in Python, with basic knowledge of C# .Net.
• Hands-on experience with tools such as Airflow, dbt, dlt, and Snowflake.
• Understanding of modern integration patterns like REST APIs and Apache Kafka.
• Experience with Data Warehouse and Data Lakehouse technologies.
• Knowledge of cloud architecture and CI-CD pipelines.
• Fluent in English.

Responsibilities

• Design, develop, and maintain end-to-end data solutions and pipelines.
• Understand domain data and support modeling to integrate data into a broader context.
• Create frameworks or reusable modules to accelerate business value creation.
• Refactor existing data pipelines and reporting solutions to new platforms and technologies.
• Leverage AI to enhance data engineering processes.
• Actively participate in value stream ceremonies, including product increment planning and status updates.
• Identify and advocate for technological transformation initiatives within the business domain.

Skills

• Strong data engineering skills with a focus on applying best practices.
• Experience with dev/data-ops methodologies.
• Curiosity for adopting new technologies and tackling challenges in a hybrid environment.

Education

• Relevant degree in Computer Science, Engineering, or a related field is preferred.

Tools

• Familiarity with data engineering tools and technologies, including Airflow, dbt, Snowflake, and cloud services.