Data Engineer
Description
This role is offered on a Contract-to-Hire basis, with an initial pre-defined contractual period. Upon successful completion of this period, the position is intended to transition to Burckhardt Compression’s permanent payroll.
Main responsibilites and tasks:
- Develop and operate the Azure Databricks data platform and enterprise data lake for analytics, AI and production data products.
- Design, implement and optimize production-grade data pipelines and transformation workflows using Python, SQL, PySpark and, where required, Scala.
- Translate business requirements into scalable ingestion, transformation, mapping and data-quality solutions.
- Administer Databricks workspaces, Unity Catalog, identities, permissions, clusters, jobs and platform integrations.
- Maintain the supporting Azure infrastructure, connectivity, security configuration and infrastructure-as-code deployments.
- Ensure reliable platform operations through monitoring, troubleshooting, upgrades, incident recovery and controlled production changes.
- Manage platform cost, technical documentation and operational continuity in collaboration with Data Science, MLOps, Cloud Infrastructure and Cybersecurity teams.
- Potentially extend development and operations scope into Microsoft Fabric for business intelligence and AI use cases.
- Strong data-engineering skills in Python, SQL and PySpark; Scala knowledge is an advantage.
- Hands-on experience with Azure Databricks, Apache Spark, Workflows, clusters, runtime management and performance tuning.
- Strong knowledge of Unity Catalog, cloud storage, identities, access controls and external locations.
- Practical Azure experience covering storage, networking, private endpoints, containers, identities and secrets.
- Experience with Terraform, Azure DevOps, Git, CI/CD and controlled production deployments.
- Ability to build and support scalable batch, event-driven and container-based data pipelines integrating files, APIs, IoT and cloud sources.
- Strong capability in platform security, monitoring, troubleshooting, performance optimization and cloud cost management; Microsoft Fabric, Power BI and Azure AI knowledge are advantages.
Education, Experience and Languages:
- Bachelor’s or Master’s degree in computer science, data engineering, software engineering or a comparable technical discipline.
- 5–8 years of relevant data engineering experience, including at least 3 years with Azure Databricks, Apache Spark and Azure cloud services.
- Proven experience developing and operating production data platforms, including data integration, modelling, performance tuning and DevOps practices.
- Experience in an industrial environment and with IoT or machine-generated data is preferred.
- English proficiency at B2 level or higher; German is an advantage.
Burckhardt Compression creates leading compression solutions for a sustainable energy future and the long-term success of its customers. The Group is the only global manufacturer that covers a full range of reciprocating compressor technologies and services. Since 1844, its passionate, customer-oriented and solution-driven workforce has set the benchmark in the gas compression industry.
Skills
- AI
- Analytics
- API
- Azure
- Azure DevOps
- Business Intelligence
- CI/CD
- Cloud
- Cybersecurity
- Data Engineering
- Data Lake
- Data Pipelines
- Data Quality
- Data Science
- Databricks
- DevOps
- Event Driven Architecture
- Git
- Infrastructure as Code
- IoT
- Microsoft Fabric
- MLOps
- Networking
- Power BI
- PySpark
- Python
- Scala
- Spark
- SQL
- Terraform
- Unity
- Unity Catalog