The corporate Vision & Strategy 2030 enables our client to focus on fully integrated lifting solutions enabled by digitalization with hard- and software from one single source. The Global Organization (GPO) is complemented with a new dedicated Digital Product Line (DPL): close cooperation with product line management & engineering (PLM&E), sales & service, process & quality management (PQM), corporate ICT and the Incubator P21st is anticipated.

The DPL’s mission is to offer digital products & services that complement our client’s existing world-class lifting solutions. Therefore, the DPL is accountable for the entire digital product life cycle which includes in-depth understanding of customer needs derived from jobs-to-be-done. New revenue streams via data-driven business models are pursued.

They are searching for a cloud-native Data Engineer that complements our expert team of data / cloud / AI/ML engineers & data scientists. Within the competence team you will be responsible for developing, testing, and maintaining data architecture and pipelines to ensure a smooth operation. The role’s focus is to work closely with our client’s experts from R&D, Product Line Management as well as corporate ICT to understand data requirements and ensure data quality and accuracy. They’re looking for a communicative, dynamic & self-reliant person whose expertise lies within data engineering in conjunction with the love for finding new technical solutions within a dynamic environment.

TASKS & RESPONSIBILITIES

Data Engineering

• Design, build and maintain data provisioning for data analytics processes
• Develop and maintain data acquisition from various sources (Cloud Storage, Line-of-Business applications like ERP/CRM, Databases, internal and external APIs, …)
• Collaborate with cross-functional teams to understand data needs and requirements
• Definition / documentation of data structures / data models / data lifecycle management
  • Implementation of Data Visualization, Reports, Dashboards

Cloud Engineering

• Deploy and maintain cloud-based data services to handle structured and unstructured data
• Optimize data storage and retrieval processes for efficiency and cost-effectiveness
• Monitor and troubleshoot data pipelines and infrastructure to ensure smooth operations; (in the sense of 2nd/3rd level support)
• Execute data transformation tasks and create and maintain a data catalogue

Data operations & data science architecture

• Actively shape/contribute the corporate data strategy together with your colleagues
• Manage the meta-data / data catalogs for data analytics
• Develop and implement ML-Ops processes aligned with CRISP-DM
• Ensure data understanding & validate the existing data quality
• Help the organization make better use of its data assets

QUALIFICATIONS

• Profound completed education in a technical field (engineering, computer science, business informatics or comparable)
• Good knowledge and experience with cloud services (Storage, Databases, Data Factory, Data Lake) and programming languages (Python, Java or Powershell)
• Good knowledge and experience with data pipelines to extract, transform, and load data from multiple sources
• Good Knowledge and experience with data-modeling and -Design skills to create efficient and effective data structures (Parquet, XML, JSON etc.)
• Knowledge working with big data technologies like Hadoop, Spark, and Hive, as well as knowledge of distributed computing and parallel processing as an advantage
• Knowledge of infrastructure as code (Azure Bicep, Terraform), data warehousing concepts (e.g. Azure Synapse) and agile process models (SCRUM) as an advantage
• High level of independence and good self-organization
• Communication strength, quality awareness, and team player mentality
• Fluent in English and negotiation skills in international business environment

THEY OFFER YOU

• Performance-related payment and attractive bonus systems
• Career planning and development opportunities
• Ongoing further training
• Voluntary social benefits through their company health management system