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Senior Software Engineer Python, Azure & DevOps

SkillHuset Sweden AB
Lund Heltid Data & IT
Publicerat 29 jul
Sista ansökan 14 aug
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About the role

We are looking for a Senior Software Engineer with strong hands-on experience in Python, Azure, CI/CD and modern engineering practices.

You will improve developer productivity by building internal tooling, reusable automation and scalable CI/CD solutions while supporting Azure-based data platforms. The role combines software engineering, DevOps and data-platform enablement in a cross-functional environment.

This is a hands-on engineering role. We are not looking for a pure platform administrator, architect or research-focused ML engineer.

Preferred location: Sweden

Requirement: EU citizenship

Responsibilities

– Develop Python-based automation, tooling and engineering workflows.

– Build and maintain GitHub Actions, GitHub Workflows and reusable CI/CD pipelines.

– Support Azure-based data platforms, including Databricks and related technologies.

– Improve software quality, traceability and engineering processes.

– Collaborate with engineering and platform teams to deliver scalable technical solutions.

Must-have

– Strong Python skills for production-oriented automation and tooling.

– Practical hands-on experience with Azure Databricks (approximately SFIA Level 3 or equivalent), ideally including development of notebooks, pipelines/jobs or Spark-based solutions.

– Experience with Azure data-platform technologies such as Spark, Kafka, Hadoop, schema enforcement, data quality validation or Power BI.

– Hands-on experience with GitHub Actions, GitHub Workflows and reusable workflow design.

– Solid Docker experience.

– Experience working with CI/CD in Windows and Linux environments.

– Ability to work independently while collaborating across teams.

– EU citizenship.

Meritorious

– Data governance and data modelling.

– Machine Learning model deployment.

– GitHub CLI (gh), REST APIs or GraphQL APIs.

– JFrog Artifactory or similar.

– Bash and/or PowerShell.

– Git LFS.

– GitHub Enterprise Server and self-hosted runners.

– AI-powered developer tools or agentic engineering workflows.

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