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 DescriptionPURPOSE 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
- 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
Skills Required
- Master's degree in IT or Economics
- 5-6 years of data engineer experience
- Fluent English
- Experience with conceptual, logical, and physical data modelling
- Professional experience building and maintaining physical and logical data models, including data streaming
- Proven experience with Microsoft Azure
- In-depth knowledge and/or certification in Databricks and Apache Spark
- Knowledge of Lakehouse architecture
- Designing and developing scalable ELT/ETL pipelines and data ingestion processes
- System management expertise: monitoring, disaster recovery, backup, automated testing, automated schema migration, continuous deployment
- Ability to gather requirements and write technical specifications
- Ensure and monitor high data quality and timely incident resolution
What We Do
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 15 countries through subsidiaries, 30 national gas markets, and 22 international trading hubs. MET has extensive experience in operating green (renewable) and flexible (conventional) energy assets, thus providing the widest possible support to energy transition. In 2022, MET Group’s consolidated sales revenue amounted to EUR 41.5 billion, with a total traded volume of natural gas amounting to 109 BCM and total traded electricity of 67 TWh. MET Group's 900+ employees come from 50 different countries.
