Big Data Architect hired

Description & Responsibilities

The Digital Transformation Team is looking for an experienced big data architect.

You will responsible for assessing and -in several cases- overseeing all big data architectures of the projects coordinated by the Digital Transformation Team.

This individual has the ability to design large-scale data processing systems for the enterprise and provide input on the architectural decisions including hardware and software. The Big Data Architect also understands the complexity of data and can design systems and models to handle different data variety including (structured, semi-structured, unstructured), volume, velocity

(including stream processing), and durability. The Big Data Architect is also able to effectively address information governance and security challenges associated with the system.

We’re looking for people with a proven track record in the sector, with a very strong scientific and technical experience and with a record in managing teams dealing with large, complex and unstructured data and distilling it to meaningful actions.

Key Qualifications

  • Strong experience in one or more among SQL/Relational, NoSQL, Hadoop, Memcache, Spark, Zookeeper, Kafka
  • Experience with scripting languages such as Perl, Python, PHP, and shell scripts
  • Ability to translate functional requirements into technical specifications
  • Ability to take overall solution/logical architecture and provide physical architecture.
  • Understand Cluster Management, Network Requirements, Important interfaces, Data Modeling
  • Ability to identify/support non-functional requirements for the solution
  • Understand Latency, Scalability, High Availability, Data Replication and Synchronization, Disaster Recovery, Overall performance (Query Performance, Workload Management, Database Tuning)
  • Propose recommended and/or best practices regarding the movement, manipulation, and storage of data in a big data solution, including, but not limited to data ingestion technical options, data storage options and ramifications (for example , understand the additional requirements and challenges introduced by data in the cloud), Data querying techniques & availability to support analytics, Data lineage and data governance, Data variety (social, machine data) and data volume
  • Understand/Implement and provide guidance around data security to support implementation, including but not limited to: LDAP Security, User Roles/Security, Data Monitoring, Personally Identifiable Information (PII) Data Security


  • MS degree in Computer Science or related quantitative field with +10 years of relevant experience in industry/scientific environment or Ph.D degree in Computer Science or related quantitative field and 5+ years of relevant experience in industry/scientific environment
  • Proficiency in English

Last update: 08/03/2017
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