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Remote - Data Product Engineer, Revenue Science

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Intelliswift Software, IncDoral, FL
Remote
  • Data Product Engineer, Revenue Science
  • As data product engineers in Revenue function, our mission is to build real-time and offline data products to make data better accessible and reliable while leveraging the largest-scale data processing technologies in the world
  • and then apply them to the Revenue’s most critical and fundamental data problems.
  • Building a Petabyte-scale Data Warehouse (Google Cloud Next '18) Migrated its On-Prem Analytics to Google Cloud (Google Cloud Next '18)
  • As a member of the Data Product Engineering team, you will work closely with product teams to build mission- critical data pipelines and products that are ‘source of truth’ fundamental revenue data, as well as modern data warehouse solutions.
  • You will collaborate closely with Ads Data Science, Machine Learning engineers, product managers, and many other data consumers across the company.
  • You will be a part of an early-stage team and have a significant stake in defining its future with a considerable potential to impact all of revenue and hundreds of millions of users.
  • You will be among the earliest adopters of bleeding-edge data technologies, working directly with Revenue Science and Revenue Platforms teams to integrate your services at scale.
  • Your efforts will reveal invaluable business and user insights, leveraging vast amounts of revenue data to fuel numerous teams including Ads Analytics, Ads Experience, Ads Data Science, Marketplace, Targeting, Prediction, and many others.
  • You are passionate about data and driven to take the data organization challenges data scope.
  • Strong programming and algorithmic skills
  • Experience with data processing (such as Hadoop, Spark, Pig, Hive, MapReduce etc).
  • Proficiency with SQL (Relational, Redshift, Hive, Presto, Vertica)
  • Data Modeling and ER models
  • Ability in managing and communicating data project plans and requirements to internal clients
  • Experience writing Big Data pipelines, as well as custom or structured ETL, implementation and maintenance
  • Experience with large-scale data warehousing architecture and data modeling Proficiency with Java, Scala, or Python
  • Experience with GCP (BigQuery, BigTable, DataFlow)
  • Experience with Druid or Apache Flink
  • Experience with real-time streaming (Apache Kafka, Apache Beam, Heron, Spark Streaming)

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