Data Engineer (REF5635Y)

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Additional Information

Our Data Tribe's mission is to deliver business value in all strategic areas of TDG to become a real data-driven company. In the Data Domain Consumer we focus on Deutsche Telekom's private customers and create exceptional consumer experience by harnessing and analyzing data to drive insights-based decision-making. In detail our value streams and teams provide personalized customer dialogue at every touchpoint. Omni-channel with the customer in the center of data-driven actions and offers to increase the customer lifetime value of all our private customers. Establishing and maintaining a single source of truth around our customer. They ensure a unified data flow of TV-relevant data across the different systems to enable holistic analytics with respect to usage, performance and customer experience. We focus on all activities around customer experience, including NPS analytics and dashboards, NPS Feedback analytics as well as adhoc analytics for CX Outerloops. Teams provide data analytics use cases for our digital touchpoints of the German NatCo and establish a common way, how generative AI should be used by enabling and supporting use cases such as NPS-X check, including use case or Telekom-specific large language model (LLM) adoptions. As a data engineer you will be responsible to develop and operate our data pipelines and build data layers in OneDataLake (ODL) our Central Data Store Consumer (CDSC). You will be responsible to balance business and IT demands to build modern and efficient pipelines in public cloud environments. You will integrate data preparations into managed processes and implement data integrations in Data Vault. Furthermore you'll be responsible for the implementation of data exports and data operations. We use Python, PySpark, SQL, libraries as Pandas, Matplotlib, Seaborn, Bokeh, Plotl and pipelines based on Gitlab (Magenta CI/CD) Essential Requirements: Minimum 3+ years of professional experience as a Data Engineer with proven expertise in big data pipelines and data processing Advanced proficiency in SQL, Python, and PySpark for hands-on data transformation and pipeline development Demonstrated experience with Git version control and CI/CD practices Strong capability to design, build, operate, and troubleshoot data pipelines in production environments Proven ability to understand complex data structures and transform them into required structural formats Business-fluent English language skills Desirable Qualifications: Senior-level experience or equivalent seniority in data engineering Hands-on experience with Google Cloud Platform (GCP) technology stack Familiarity with Hadoop ecosystem and related big data technologies Experience with data modelling, exploration, and architecture within enterprise environments German language proficiency Key Competencies: Practical, hands-on approach to problem-solving (not purely conceptual or advisory) Ability to quickly assimilate complex data environments and deliver solutions Experience integrating data preparations into managed processes and implementing Data Vault integrations Familiarity with data visualisation libraries such as Pandas, Matplotlib, Seaborn, Bokeh, and Plotly * Please be informed that our remote working possibility is only available within Hungary due to European taxation regulation.

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