As Senior Data Engineer (m/f/d) in the Data Intelligence BU, you will be responsible for the (further) development of marketable industry-specific and cross-industry platforms and platform-based products, for the overall target architecture of the core platforms and platform-based products, and for the application operation of platforms and products of T-Systems. You will actively shape the future of the Magenta Data Analytics /Data-Economy portfolio.
This includes the following responsibilities
- Leads data engineer team, act as thought leader and work with product management to help drive appropriate product enhancements and develop roadmaps and architecture strategy
- Designs, builds, integrates data from various resources into datamarts & warehouses. Builds large scale data processing pipelines
- Uses automated software frameworks for data acquisition, validation, blending and modeling - make sure data is accessible and cleaned for further analysis
- Proven track-record in building data workflows and data products. Defines big data architecture (ingest, store, analyze, visualize etc.) and specifies technical requirements on product design. Leads development of solution design of IOT architecture
- Optimizes performance of big data systems and researching how Spark, Kafka, Hadoop (HDFS, Hive), Flink, Cassandra and other distributed systems can work together at scale. Comes up with entirely new ideas to build world class data integration systems one step ahead of the industry
- Proficient in designing efficient and robust ETL workflows (Extract, Transform, Load) on top of big datasets and create big data warehouses that can be used for reporting or analysis by data scientists
Background and required skills:
- Has a PhD or master’s degree in Data Science, Physics, Mathematics, Statistics or Computer Science with at least +3 years of professional experience in the field of data analytics & data economy, ideally experience with the Telekom Data Intelligence Hub
- Experience in working in large agile environments (SAFe, SCRUM, DevOps, Clean Code)
- Has advanced experience & competence to design and manage big data environments (e.g., Hadoop), evaluate and configure components (e.g., Spark, DB), adapt and code algorithms for customer solutions (at least 5 years). Hands-on experience with big-data eco-system – at least one of them: Hadoop, map/reduce, yarn, apache spark, kafka, flink, storm, nifi (at least 5 years)
- Knowledge in mathematics and statistical methods is required (at least 3 years). Experience in two of the following methods are desirable: clustering, classification, modeling, regression, text analysis, pattern recognition, neuronal networks. Understanding of machine learning principles and methods
- Knowledge of privacy and security challenges and solutions in IOT and data analytics, e.g., privacy by design, anonymization, privacy preserving storage (at least 3 years)
- Experience in two of the following application areas are required: IOT analytics, time series analytics, social media analytics, location data analytics, security data analytics, customer data analytics, signal processing, anomaly detection (at least 3 years)
- Advanced experience in cloud architectures, computing services (network, storage), application operations and development (java, Python, Jupiter) on large scale data lake solutions. Experience in deploying and managing large-scale distributed systems (at least 5 years)
- Experience in deploying and managing large-scale distributed systems. Forward Thinking in your ability and interest in translating business requirements into technological visions, and reimagining data-processing technologies (at least 5 years)
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