Responsibilities:

  • Selecting and integrating any Big Data tools and frameworks required to provide requested capabilities
  • Implementing ETL process
  • Creating DWH architecture
  • Implementing DWH architecture
  • Monitoring performance and advising any necessary infrastructure changes
  • Defining data retention policies

Requirements:

  • Proficient understanding of distributed computing principles
  • Management of Hadoop cluster, with all included services and configuration of associated hardware and software
  • Python knowledge, might be Scala
  • Proficiency with Hadoop or Cassandra, Map Reduce, HDFS
  • Experience with building stream-processing systems, using solutions such as Storm or Spark-Streaming
  • Good knowledge of Big Data querying tools, such as Pig, Hive, and Impala
  • Experience with Spark
  • Experience with integration of data from multiple data sources
  • Experience with NoSQL databases, such as HBase
  • Experience with RDBMS’s like Oracle and MySQL
  • Knowledge of various ETL techniques and frameworks.
  • Experience with various messaging systems, such as Kafka- Experience with Big Data ML toolkits, such as Mahout, SparkML, or H2O
  • Good understanding of Lambda Architecture, along with its advantages and drawbacks
  • Experience with Cloudera/MapR/Hortonworks would be an advantage

Personal skills:

  • Working well autonomously, without close supervision, readiness to take responsibility
  • Acting as a Team player and having highly developed communication skills, both toward co-programmers and project manager
  • Being committed to timely delivery of quality results
  • Innovative in his/her work
  • Knowledge seeking, updated with regards to latest SDK and technological directions in general
  • Documenting his code and general functionality

Desirable:

  • Graduate in quantitative scientific, engineering and/or mathematical discipline (Mathematics generally, Statistics/Probability, Physics, Electrical Engineering, Experimental Psychology, Chemistry, etc.) ––demonstrable deep knowledge in quantitative principles
  • Significant experience working closely with business subject matter experts (SME) to achieve business outcomes
  • Experience in contributing to data monetization strategy
  • Ability to appreciate business questions, not just the science
  • Have generated significant IP (internal/proprietary, patents, academic or business journal publications)
  • Track record in innovation / expertise is data engineering
  • Some experience managing at least 3 people for any given project
  • Comfortable with significant travel when needed
  • Personable / experience with direct customer interactions
  • Very entrepreneurial by nature, experience in startup culture including working on an onshore/offshore model

You will get:

  • Career growth opportunities
  • Friendly collaborative teams and enjoyable working environment
  • Professional skills development and training programmes
  • Variety of knowledge sharing, training and self-development opportunities
  • State of the art, cool, centrally located offices with warm atmosphere which creates really good working conditions