Data Engineer

Falck's Data, Insights & AI department brings together experts in data engineering, analytics, AI, automation, and business partnering to support a global healthcare and emergency services organisation. With 60+ professionals in Copenhagen and Warsaw hubs, they build data and AI solutions that are reliable, scalable, and actually used. The role is part of the mission-critical Data Platform team providing shared standards and frameworks to accelerate delivery for the entire organization.

• A few years of professional experience in data engineering or platform engineering.
• Demonstrated ability to work independently on routine, well-defined data engineering tasks.
• Experience taking on more complex tasks with guidance and support from senior team members.
• Solid hands-on experience with Azure, Databricks, PySpark, Python, and SQL.
• Proven ability to build and maintain data pipelines for various common data sources.
• Good understanding of data modeling concepts and their practical application.
• Comfortable using CI/CD pipelines for deployment and pragmatic in troubleshooting.
• Good communication skills in English.

Platform & Framework Development:

• Design, build, and maintain core data pipelines and reusable frameworks using PySpark, Python, and SQL on the Databricks platform.
• Develop foundational platform components that enable other teams to build their data solutions faster and more reliably.
• Help integrate a wide variety of data sources into the platform in a standardized and scalable way.

Ensuring Quality & Reliability:

• Take ownership of code quality by writing unit tests, performing peer code reviews, and contributing to technical documentation.
• Investigate and resolve bugs and performance issues in core platform components, seeking support from senior engineers when needed.
• Contribute to team-level standards for code, templates, and infrastructure to improve platform robustness.

Using and Improving our Platform:

• Work with core components of the data platform, Databricks and PySpark, to build and optimize data processing tasks.
• Use CI/CD pipelines to deploy platform services to Azure cloud and independently investigate and resolve common pipeline failures.

Team Collaboration & Growth:

• Collaborate daily with other engineers on the platform team and with engineers in other teams using the frameworks.
• Act as a source of advice for junior team members on standard technical issues and help onboard new colleagues.
• Proactively seek and incorporate feedback from seniors and peers to drive learning and professional development.