Siemens Careers

Big Data Software Engineer

Princeton, New Jersey
Research & Development

English (US)

Job Description

Division: Corporate Technology
Business Unit: Corporate Technology
Requisition Number: 221409
Primary Location: United States-New Jersey-Princeton
Assignment Category: Full-time regular
Experience Level: Mid level
Education Required Level: Master's Degree
Travel Required: 10%

Division Description:

For nearly 170 years, pioneering technologies and the business models developed from them have been the foundation of Siemens‘ success. Our central research and development unit, Corporate Technology (CT) plays an important role in this. Together with our global network of experts, we are a strategic partner to Siemens’ operative units and provide important services along the entire value chain – from research and development to production and quality assurance, as well as optimized business processes. Our support provided to the businesses in their research and development activities is ideally balanced with our own future-oriented research.

We at Corporate Technology are more than employees: We are actively helping to make people’s lives a little better every day. Would you like to be a part of that? Then join us. We offer you a high level of practical relevance as well as an opportunity to individually contribute your knowledge and your visions around the world. Whether you’re helping to develop products for the operating units or working in interdisciplinary projects for the business areas: At Corporate Technology you’ll be working in the heart of Siemens’ technological research together with the best.

Job Description:

We are seeking an Engineer in Big Data Analytics and Machine Learning to be part of our growing Information Integration and Business Intelligence (IBI) Team which is part of the exciting and world-wide distributed Technology Field of Business Analytics and Monitoring.

The Information Integration and Business Intelligence Research Group focuses on exiting cutting edge technologies in big data analytics and machine learning to gain exceptional business insights from tremendous amount of data and data-sources to improve the competitiveness of Siemens Business Units to generate innovative new products and business models used around the world. 

This Engineer in Big Data Analytics will contribute to our research activities by applying modern data analytics and machine learning on variety of structured and unstructured data from wide area of different industries such as automation, energy, healthcare, building automation and mobility with the goal to improve business insights and help various business units to gain competitive advantage in their markets.

The Engineer in Big Data Analytics will be responsible for developing new algorithms and code prototypes as proof of concept in the new research area of Security, Safety and Compliance in collaboration with our security research group and also contribute to current analytics research for business analytics and monitoring.


• Research, design, and implement algorithms that power knowledge inference and online recommendations, based on Deep Learning/machine learning to consume various types of data.
• Dive into huge, noisy, and complex real-world behavioral data to produce innovative analysis and new types of predictive models of engineering behaviors and manufacturing processes performance.
• Explore the untapped potential of big data for design, engineering and analysis tasks and devise revolutionary approaches.
• Advance the state-of-the-art in the field, including generating patents and publications in top journals and conferences.
• Apply deep learning techniques to large-scale, real-world problems.
• Fast prototyping, feasibility studies, specification and implementation of data analysis product components.
• Working with customers to understand algorithm requirements and deliver high-quality solutions.

Required Knowledge/Skills, Education, and Experience

•Master degree with 3+ years of Experiences in the field of Big Data Analytics is required.
•Software development in Java is required.
•Strong proficiency in Big Data tools and their configuration & setup is a plus. 
•Strong proficiency in NoSQL databases (e.g MongoDB, Cassandra, etc). 
•Experienced in ETL tools (e.g Talend, Spring Batch, Informatica, etc). 
•Proficiency in Knime, Hadoop and Spark
•Capability for quick prototyping.
•Outstanding written and verbal communication skills in English are required.
•Excellent interpersonal skills and a can-do attitude.
•Strong collaboration skills and ability to thrive in a fast-paced environment.
•Flexibility and adaptability to work in a growing, dynamic team.

*Please include a detailed copy of your resume when applying*

•Ability to work with controlled technology in accordance with US export control law required. Siemens may require candidates under consideration for employment opportunities to submit information regarding citizenship status to allow the organization to comply with specific US Export Control laws and regulations. Additional information on the US Export Control laws & regulations can be found on

Preferred Knowledge/Skills, Education, and Experience

•Degree in Computer Science or Information Technology preferred. 
• Proficiency in security and compliance analytics preferred.
• Previous experience or knowledge in the field of probabilistic reasoning, uncertainty quantification, dimensionality reduction, decision trees, and design analysis is preferred.
• Previous experience or knowledge in the field of machine learning/deep learning.


Equal Employment Opportunity Statement
Siemens is an Equal Opportunity and Affirmative Action Employer encouraging diversity in the workplace. All qualified applicants will receive consideration for employment without regard to their race, color, creed, religion, national origin, citizenship status, ancestry, sex, age, physical or mental disability, marital status, family responsibilities, pregnancy, genetic information, sexual orientation, gender expression, gender identity, transgender, sex stereotyping, protected veteran or military status, and other categories protected by federal, state or local law.

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