Big Data Architect

  • Argentina
  • Buenos Aires
  • Rosario
  • Belarus
  • Minsk
  • Brazil
  • Sao Paulo
  • Chile
  • Santiago de Chile
  • Colombia
  • Bogota
  • Medellin
  • France
  • Paris
  • India
  • Pune
  • Mexico
  • Ciudad de México
  • Peru
  • Lima
  • Romania
  • Cluj-Napoca
  • Spain
  • Madrid
  • Uruguay
  • Montevideo
  • Buenos Aires
  • Rosario
  • Minsk
  • Sao Paulo
  • Santiago de Chile
  • Bogota
  • Medellin
  • Paris
  • Pune
  • Ciudad de México
  • Lima
  • Cluj-Napoca
  • Madrid
  • Montevideo

We are a digitally native company where innovation, design and engineering meet scale. We use the latest technologies in the digital and cognitive field to empower organizations in every aspect. We want you to join us to work for the biggest clients in tech, retail, travel, banking, ecommerce and media, revolutionizing and growing their core businesses while helping them (and you!) stay ahead of the curve. Be part of a company with the most cutting-edge practices and technologies plus a unique team. Globant is an EOE M/F/D/V. For many positions relocation is available if needed. Globant does not accept unsolicited 3rd party resumes.  

What Are We Looking For?

Bachelor's Degree in CS, Information Technologies or related technical field.
3+ years as a software engineer. 
Strong experience in data modeling in the Big Data field, dealing with big volumes of data. 
Hands on experience with Hortonworks, Cloudera, MapR and/or Apache Hadoop distribution. 
Understanding of Big Data concepts: HDFS/YARN architecture, MapReduce steps, CAP theorem, high performance analytics, Batch/NRT solutions, etc.

What Will Help You Succeed

Experience with NoSQL databases such as Apache HBase, MongoDB or Cassandra. Experience with Apache Spark. 

You Will Get The Chance To

Design and implement Data Platforms for large-scale, high performance and scalable requirements, integrating data from several data sources, managing structured and unstructured data while melding existing warehouse structures. 
Analyze, diagnose and identify bottlenecks in data workflows. Identify and evaluate current data management technologies. 
Create business models and develop distributed data solutions. 
Participate in demos and trainings to clients as well as requirements elicitation and traduction to systems requirements (functional and nonfunctional). 
Constantly monitor, refine and report on the performance of data management systems. 
Provide Feedback and Status to the Infrastructure and Support Teams. 
Contribute to the Digital Services Platform roadmap. 
Work with the Support Team on Critical Issues.