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Skills: Data Modeling, MS Azure, Lakehouse Architecture, Databricks, Apache Spark
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Senior+$1.7B raised
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Lead Analyst, Third-Party Risk & Operational Resilience
Budapest, Central Hungary, Hungary · Hybrid
$14769k–$24762k/yr
Senior$3.5B raised
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Full-time
postgraduate degree
Posted 1d ago
~40 hrs/week
Responsibilities
The Data Engineer is responsible for designing, developing, and maintaining scalable ELT packages and data pipelines within the data analytics platform. They act as the platform architect, defining logical and physical data models to ensure data availability and re-usability for analytics products.
Requirements
Candidates must hold a Master's degree in IT or Economics and possess 5-6 years of experience in data engineering. Proficiency in MS Azure, Databricks, and conceptual data modeling is essential.
Full job description
Company Description
MET Group is an integrated European energy company, headquartered in Switzerland, with activities in natural gas and power, focused on multi‑commodity wholesale, trading and sales, as well as energy infrastructure and industrial assets.
The Group is represented in 24 countries: Albania, Austria, Belgium, Bosnia and Herzegovina, Bulgaria, Czech Republic, Croatia, France, Germany, Greece, Hungary, Italy, North Macedonia, Moldova, Poland, Romania, Serbia, Singapore, Slovakia, Spain, Switzerland, The Netherlands, Turkey and Ukraine.
MET is present in 33 national energy markets and 51 international trading hubs. The Group has a significant end‑consumer presence in Belgium, Croatia, Italy, Hungary, Romania, Slovakia, Spain, and The Netherlands.
The company has 1400+ permanent staff. The company is owned 90% by MET employees and 10% by Keppel Infrastructure, a wholly owned subsidiary of Keppel Corporation.
Listed on the Singapore Exchange
Job Description
PURPOSE OF THE POSITION
The Data Engineer is responsible for the maintenance and the improvement of all the data flows in the data analytics platform(s). The Data Engineer designs and develops scalable ELT packages and routines from the source systems in order to create information (datasets), defining and building the data pipelines.
The Data Engineer additionally analyzes complex data models and IT Applications, data flows, dependencies and relationships in order to contribute to conceptual physical and logical data models.
Moreover, the Data Engineer acts as architect of the Data & Analytics platform defining the logical data model and the physical data model(s). He/She also keeps up with industry trends and best practices, advising the management on new and improved data engineering strategies.
Main responsibilities
Define the optimal architecture of the Data & Analytics platform enabling the availability and re-usability of all required data for the creation of analytics products
Manage and monitor data pipelines to source and transform data to the Data & Analytics Platform(s)
Integrate and transform new data sources (internal and external) by creating a full pipeline from ingestion to ETL process
Deliver Data Provisioning to operational applications requiring transformation of data from several sources
Optimize and expand the Data & Analytics platform data flows and data models, supporting in deploying analytics products
Define and document detailed Data Engineering processes to guarantee efficient building and support of the data & analytics platform
Assess the stability, robustness and efficiency of the implemented ELT processes and data pipelines and eventually re-design them
Gather requirements and write technical specifications document
Ensure and monitor high data quality standards with focus on data consistency
Timely resolve incidents related to data interfaces and ELT processes
Expand the current Data & Analytics platform to embed “big data” capability by investigating and sharing best practices
Qualifications
Master’s degree in IT / Economics
5-6 years of data engineer experience
Fluent English
Experience with data modelling (conceptual, logical, physical) and data modelling documentation
Professional experience and conceptual knowledge of building and maintaining physical and logical data models, including data streaming
Ability to think beyond technology requirements to build ONE logical Data & Analytics platform
Excellent knowledge and proven professional experience with MS Azure and Lakehouse architecture, in-depth knowledge and/or certification in Databricks (Spark)
Well structured, analytically thinking and demonstrating the ability to explain processes in a clear and understandable manner to a non-technical audience
System management expertise with monitoring, disaster recovery, backup, automated testing, automated schema migration, and continuous deployment
Ability to take ownership and proven strive for excellence
MET Group is an integrated European energy company, headquartered in Switzerland, with activities and assets in natural gas and power markets.
MET is present in 24 countries through subsidiaries, 33 national energy markets, and 51 international trading hubs. The company's 1,400+ employees represent close to 60 nationalities.
MET has extensive experience operating renewable and flexible assets, thus providing the widest possible support to energy transition.
In 2025, MET Group traded 242 BCM of natural gas and 160 TWh of electricity.
How many Data & Analytics jobs are open in Budapest, Hungary right now?
There are currently 455 open data & analytics positions in Budapest, Hungary listed on Clera. New openings are added daily as companies post roles.
Which companies are hiring for Data & Analytics roles in Budapest, Hungary?
Companies currently hiring include bp, MOL Group, Deutsche Telekom IT Solutions HU, OTP Bank Magyarország, ALDI SÜD, among others. Browse the listings above to see every active employer.
Are there remote or hybrid Data & Analytics jobs in Budapest, Hungary?
Yes — 329 of the 455 open data & analytics positions offer remote or hybrid work (46 remote, 283 hybrid).
How do I apply for Data & Analytics jobs in Budapest, Hungary?
Each listing links directly to the employer's application page. Apply early — fresh listings get the most recruiter attention in the first two weeks.