Senior Data Engineer driving data intelligence requirements and scalable data solutions for a global consulting firm. Collaborating across functions to enhance Microsoft architecture and analytics capabilities.
About the role
- Data Management Engineer managing product data for optical transmission technologies at Nokia. Collaborating with cross-functional teams to drive innovation and enhance product development.
Responsibilities
- oversee part requests and manage the Bill of Materials (BOM) for accurate product development data management.
- ensure the accuracy, consistency, and integrity of product data across all platforms and processes.
- support the introduction of new Product Data Management (PDM) systems, defining requirements for successful integration.
- conduct user acceptance testing (UAT) to validate new processes and drive improvements in data management systems.
- simplify and automate PDM processes to enhance efficiency and reduce the time for data-related workflows.
- perform data analysis to extract insights and generate actionable reports, informing key business decisions.
- collaborate with cross-functional teams to align on data strategies, fostering a culture of data quality and excellence.
- lead initiatives to continuously improve data governance practices, enhancing overall product development efficiency.
Requirements
- University degree in Mechanical or Electrical Engineering or Business Administration
- Analytical and structured thinking, high problem-solving skills
- Teamwork and experience in coordinating various stakeholders
- Expertise in PDM tools e.g. Enovia R2014x, Agile PLM, Aras Innovator, PTC Windchill, etc.
- Deep expertise in Microsoft Office tools
- English and German fluently spoken and written
- Ability to work independently and self-organized
- Good communication skills
- It would be nice if you also had:
- Expertise in collaboration with EMS partners or suppliers on prototype and volume production
- Expertise in electrical or mechanical design and technical documentation of telecom hardware
- Expertise in data analysis, data classification, data formats and data structures
- Knowledge in scripting languages, e.g. VBA, Python, Perl, SQL.
Benefits
- flexible work arrangements
- professional development opportunities
- comprehensive benefits package
- health and wellness programs
- employee discounts
- generous time-off policies
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
Experienced AI Engineer designing and building production - grade agentic AI systems using generative AI and large language models. Collaborating with data engineers, data scientists in a tech - driven company.
Intermediate Data Engineer designing and building data pipelines for travel industry data management. Collaborating across teams to ensure reliable data for analytics and reporting.
Data Engineer managing and organizing datasets for AI models at Walaris, developing AI - driven autonomous systems for defense and security applications.
Data Engineer designing and maintaining data pipelines at Black Semiconductor. Collaborating with process, equipment, and IT teams to support manufacturing analytics and decision - making.
Junior Data Engineer role focusing on Business Intelligence and Big Data at Avanade. Collaborating on data analysis and SQL queries in a supportive learning environment.
GCP Data Engineer designing and developing data processing modules for Ki, an algorithmic insurance carrier. Working closely with multiple teams to optimize data pipelines and reporting.
Data Engineer at Securian Financial optimizing scalable data pipelines for AI and advanced analytics. Collaborating with teams to deliver secure and accessible data solutions.
IT Data Engineering Co‑Op at BlueRock Therapeutics supports development of scientific data systems. Collaboration on data workflows and foundational AWS data engineering tasks.
Data Engineer I building and operationalizing complex data solutions for Travelers' analytics using Databricks. Collaborating within teams to educate end users and support data governance.