Design, develop, and maintain squad-specific data architectures and pipelines following ETL and data lake principles. Develop data products for analytics and ML engineers while mentoring other data professionals on standards and best practices.
PLACE OF WORK
1112 Budapest, Boldizsár utca 2.
AREA OF EMPLOYMENT
IT
START OF WORK
as soon as possible
EMPLOYMENT TYPE
Full-time
megállapodás szerint
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.
“I was the first applicant for a remote marketing position that got listed on the company website the same day I applied. Had an interview within 48 hours!”
— Sarah J.
·
Marketing Manager
★★★★★
Verified
