Big Data Engineer - Monster Worldwide

Prague 18600, Prague Csehország

Az állásról

With more than 600 employees located in development centers in the U.S., Europe, India and Malaysia, Monster Technologies fosters an innovative and entrepreneurial environment focused on leveraging cutting-edge technology to develop industry-leading products for private businesses. Monster takes its cutting edge technologies and adapts them for clients as well as develops new products to fit its clients unique hiring and recruiting needs.


Are you a fast and eager learner? Do you enjoy working with new technologies? Are you a proven technologist and architect with a passion for data in all its shapes and sizes? Do you have a desire to provide high quality solutions and best practices? The successful candidate will be someone who is intellectually curious and able to take the initiative and find creative solutions to business problems. We are looking for someone who not only embraces change, but who accelerates it.


Monster is looking for an exceptional Big Data Engineer to join our fast growing Development Group. We are a dynamic, talented, and passionate team looking for highly talented individuals. We create and support complex algorithms to perform large-scale distributed data processing on our high performance clusters. If you are excited to create solutions to minimize business risks and tackle complex real-world challenges, this is the right opportunity for you!

This is a fantastic opportunity for an experienced engineer to combine data engineering and data science, and get exposure to the latest tech available.


The Role

  • Provide recommendations on optimizing & improving data relevance, search functionality, user behavior analysis
  • Improve, implement test theories; transform theories, showcase measurable results on improving search functionality and user experience
  • Work as part of an Agile / Scrum team
  • Develop algorithms to perform data fusion and data analysis in very large scale distributed environment
  • Create infrastructure/tools to enable management and efficient processing of large amounts of data
  • Provide technical and architectural leadership for excellent big data and analytics services
  • Support the creation of collateral and operational best practices materials
  • Answer technical queries from / liaise with, all other stakeholders on technical matters.


Must have skills

  • Degree in Engineering/Computer Science, Sciences or Mathematics. Alternatively a proven track record of delivering complex or cutting edge solutions within the IT industry
  • Good knowledge of various database systems from which data science tasks might draw data (Hadoop, SQL, NoSQL, Graph, Lucene, Streaming)
  • Hands on experience using R/Python for data science
  • Good software engineering practices (appreciate the importance of good coding practices to DS, unit testing, version control, code review…)


Good to have

  • Detailed knowledge on a range of machine learning techniques. Implementing statistical and machine learning algorithms efficiently.
  • Data visualization experience
  • Designing data analytics pipelines processing Terabytes of data
  • Good understanding of data manipulation/wrangling techniques
  • Nice to have interest in Natural Language Processing
  • Cloud such as AWS/Azure



  • Links to open-source project you actively participated in
  • Profile on if available


What Monster Offers:

  • International working environment.
  • A 25 day vacation package.
  • Competitive salary.
  • Relocation assistance.
  • Company benefits; including life insurance, language courses, food vouchers, discounted gym membership, sport activities.
  • Career progression opportunities.
  • Casual dress code


If you think you are the right person for the job, please do not hesitate to apply using the apply button below to join our global Technologies Team.


Edzőtermi bérlet
Munkavállalói események
Ingyen kávé
Még több előny
Továbbküldés e-mailben
E-mail küldése
Megjegyzés: Az e-mail címet csak ezen egy alkalommal használjuk fel.