Data Engineer (Databricks, PySpark, SQL)
Debrecen Mid-level Data Engineering
At a glance
Mid-level Data Engineering role at ALDI. Debrecen.
Pay not stated Data Engineer salary
RoleData Engineering
SeniorityMid-level
LocationDebrecen
PostedSep 6, 2026 · 6w ago
Role brief
dataroles summary, based on the employer's posting.
What you'll do
- Build and improve squad data pipelines and architectures using ETL and data lake approaches
- Package pipeline and architecture materials for the platform team to reuse across squads
- Create analytics data products that help analysts, data scientists and ML engineers work more effectively
- Guide data and analytics colleagues on standards, and help assess new engineering tools and improve practices
What you bring
- A computer science degree or a related qualification
- At least ten years in software or infrastructure development, including four or more in data engineering
- Strong SQL and data analysis skills, plus proficiency in a language such as Python or Scala
- Practical Azure data platform experience, including Databricks and Data Factory, alongside distributed computing knowledge
- Fluent English and experience with data modeling, databases and ETL concepts
Who this fits
This role suits an experienced data engineer who can shape shared data practices and support colleagues, not only build pipelines. It is full-time and based in Debrecen, with remote work options and flexible hours.
From the employer
- PLACE OF WORK
- 4024 Debrecen, Barna utca 23
- AREA OF EMPLOYMENT
- IT
- START OF WORK
- as soon as possible
- EMPLOYMENT TYPE
- Full-time
My responsibilities:
- Design, develop, optimize, and maintain squad-specific data architectures and pipelines in line with ETL and data lake principles
- Prepare, align, and hand over data architecture and pipeline artefacts to the platform team for reuse across squads
- Solve complex technical data challenges that support business objectives
- Develop data products for analytics, data scientists, and ML engineers to improve productivity within the team and across the organization
- Advise, mentor, and support data and analytics professionals on data standards and best practices within the squad and organization
- Contribute to the evaluation of emerging tools in data engineering and data science, helping to define and improve standards and ways of working
- Drive continuous improvement by contributing to training, capability development, and enhancements in analytical data engineering practices, standards, and processes
The knowledge I own:
- Degree in Computer Science or related field
- 10+ years of experience in software or infrastructure development, including at least 4 years in data engineering within distributed computing, big data, or advanced analytics environments
- Strong expertise in SQL and data analysis, with proficiency in at least one programming language such as Python or Scala
- Experience in database development and data modeling, ideally with Databricks/Spark and SQL Server; knowledge of relational, NoSQL, and cloud-based databases.
- Solid understanding of distributed computing concepts, preferably with Spark or MapReduce
- Hands-on experience with Azure tools such as Azure Data Factory, Azure Databricks, Event Hub, Synapse, and ML services
- Good understanding of data and analytics concepts, including dimensional modeling, ETL, data warehousing, reporting, data governance, and handling structured and unstructured data
- Familiarity with Unix systems, especially shell scripting
- Basic knowledge of network concepts, connectivity, and troubleshooting
- Foundational understanding of machine learning, data science, AI, statistics, or applied mathematics
- Strong communication skills and fluent English; German is a plus
Tech Stack
- Azure Databricks
- Azure Data Factory
- Python
- PySpark
- ServiceNow
- M365
- and other tools depending on the role
The offer that would convince me:
- We develop and maintain our own product with high emphasis on quality and long-term stability
- Code quality matters: we follow Clean Code and SOLID principles backed by robust testing
- Flexible working hours and remote work options
- Competitive salary with regular adjustments based on inflation and loyalty
- Access to continuous learning via our internal learning platform and expert communities
Online application:
Please use our online application and attach your resume.
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