Senior Data Engineer role at WALTER GROUP, based in Wiener Neudorf, Lower Austria, Austria. The company employs more than 5,000 people and IT is a key growth driver. As a Senior Data Engineer you will build scalable data solutions, integrate information from diverse sources, and provide high quality data for Analytics, Business Intelligence, and Data Science. Responsibilities include: Data Engineering — develop scalable batch and streaming pipelines; Platform & Architecture — advance the cloud data platform with a focus on scalability, performance, and cost; DataOps & Automation — implement CI/CD and orchestration processes and ensure a stable, automated operation of the data platform; Integration & Data Quality — integrate data from legacy systems, APIs, and streaming platforms, ensuring high data quality across the data lifecycle; Collaboration — work with BI, Data Science, and business units to develop powerful data products; Mentoring & Development — support colleagues with technical questions, share knowledge, and contribute to engineering standards. Qualifications: completed degree in Computer Science, Information Systems, or a comparable field; several years of experience building and operating productive data engineering solutions in cloud environments (Google Cloud Platform preferred); strong Python skills (Java a plus); experience with modern data engineering, orchestration, and CI/CD technologies; experience with cloud platforms (ideally Google Cloud), analytical databases (BigQuery), and modern data architectures such as Data Warehouses, Data Lakes, Data Marts,

Senior Data Engineer role at WALTER GROUP, based in Wiener Neudorf, Lower Austria, Austria. The company employs more than 5,000 people and IT is a key growth driver. As a Senior Data Engineer you will build scalable data solutions, integrate information from diverse sources, and provide high quality data for Analytics, Business Intelligence, and Data Science. Responsibilities include: Data Engineering — develop scalable batch and streaming pipelines; Platform & Architecture — advance the cloud data platform with a focus on scalability, performance, and cost; DataOps & Automation — implement CI/CD and orchestration processes and ensure a stable, automated operation of the data platform; Integration & Data Quality — integrate data from legacy systems, APIs, and streaming platforms, ensuring high data quality across the data lifecycle; Collaboration — work with BI, Data Science, and business units to develop powerful data products; Mentoring & Development — support colleagues with technical questions, share knowledge, and contribute to engineering standards. Qualifications: completed degree in Computer Science, Information Systems, or a comparable field; several years of experience building and operating productive data engineering solutions in cloud environments (Google Cloud Platform preferred); strong Python skills (Java a plus); experience with modern data engineering, orchestration, and CI/CD technologies; experience with cloud platforms (ideally Google Cloud), analytical databases (BigQuery), and modern data architectures such as Data Warehouses, Data Lakes, Data Marts,