Some context on our scale

- We see Millions of daily real-time events representing the living breathing internet

- We track Billions of digital assets

- We store Petabytes of event-state data

RESPONSIBILITIES

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  • Selecting and integrating Big Data tools and frameworks
  
  
  • Implementing ETL strategies
  
  
  • Monitoring performance and driving the discussion on supporting infrastructure
  
  
  • Defining data retention policies
  
  
  
  

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  • Proficient in your understanding of distributed computing principles
  
  
  • Proficient with Hadoop v2, MapReduce, HDFS
  
  
  • Experienced with building stream-processing systems, using solutions such as Storm or Spark-Streaming, Kafka
  
  
  • Experienced with Big Data querying tools, such as Pig, Hive, and Impala
  
  
  • Experienced with NoSQL databases, such as HBase, Cassandra, MongoDB
  
  
  • Knowledgeable of various ETL techniques and frameworks, such as Flume
  
  
  • Experienced with various messaging systems, such as Kafka or RabbitMQ
  
  
  • Experienced with Big Data ML toolkits, such as Mahout, SparkML, or H2O
  
  
  • Experienced with Lambda Architecture, and understanding of its advantages and drawbacks
  
  
  
  

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  • Front-End : Angular
  
  
  • Back-End: Ruby / Rails, Node
  
  
  • Data Stores: Postgres, Mongo, ElasticSearch, Dynamo, InfluxDB, Redis, Memcache, S3
  
  
  • Clouds: AWS, Heroku, DigitalOcean