DATA ENGINEER (mf/d)
At a glance
Mid-level Data Engineering role at SchwarzIT Sourcing. Sofia.
Pay not stated Data Engineer salary
dataroles summary, based on the employer's posting.
What you'll do
- Build production-ready APIs in Python and Java, and create ETL pipelines for data workflows
- Set up CI/CD pipelines and reusable templates for data products
- Add monitoring, help data teams debug issues, and deploy open-source tools on cloud platforms
- Share technical knowledge with the community and help the team establish data engineering practices
What you bring
- You have strong Python and SQL skills; Java experience is an advantage
- You have built ETL pipelines and can optimize Databricks and PySpark jobs and code
- You bring Docker and Kubernetes expertise, plus experience with GCP, StackIT and Azure
- You communicate well with stakeholders, understand adjacent data disciplines, and turn business needs into data solutions
- You speak English very well; German is optional
Who this fits
This role suits a mid-level data engineer who enjoys collaboration and sharing technical knowledge. It is based in Sofia, Bulgaria, and calls for work across Python, Java and cloud data platforms.
From the employer
Make an amazing climb in your career in an international team of experts. Our company provides technological services for the whole Schwarz group of more than 30 countries in Europe and the US. Our vision is to be the leading ecosystem for a better life. We built the European sovereign cloud STACKIT. With XM Cyber we set new standards in differing cyber crimes. We run AI better than anyone. With us you will find a variety of opportunities to grow and do your best at your calling – IT. We exist to improve life with our products and services - for today's generation and future generations. We act future proof!
The impact you will create:
- Building Scalable production-ready APIs in Python and Java - Expert in Python, SQL; Java beneficial
- Experienced in building ETL pipelines
- Building CI/CD pipeline and data product templates
- Application of monitoring capabilities
- Debugging support for data teams
- Open-source tool deployment on cloud platforms
- Community communication and technical knowledge exchange
- Support the team in establishing data engineering best practices
Experience and skills you will need:
- Docker and Kubernetes expertise
- Databricks and PySpark expert with job and code optimization
- GCP, StackIT, and Azure expertise
- Demonstrated ability in stakeholder communication and management
- Good understanding of related data disciplines (e.g. MLOps engineering, analytics)
- Ability to understand, analyze and translate business requirements into data-driven solutions
- Enthusiasm for collaboration, knowledge sharing and joint learning
- Very good English skills - German is a plus, but not a must
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