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Data Engineer

Job Description:

The ideal candidate is passionate about new and cutting-edge technologies, has a strong interest in developing data and analytics solutions to address business problems, and can build and implement combined data management and data processing infrastructure and solutions.  The person in the role should also possess some data scientist specific skills including coding expertise in general-purpose or specialized high-level programming languages, such as Python, R, Scala, or SQL.

The candidate should also have broad familiarity and knowledge of enterprise and open-source applications, technologies, and tools applicable to AI, ML, and other data pipelines.  Experience in building solutions and workflows to solve data-oriented problems commonly found in various industries such as manufacture, retail, security, healthcare, and transportation is a big plus.  Familiarity of containerized environments (Docker, K8S) will also be beneficial to the role.


  • Design and build POC and POV data pipelines for various use cases
  • Establish close technical relationships to customer accounts, building personal relationships to facilitate data solutions tailored to the end-customer use case
  • Identify applications, platforms, and tools that satisfy gaps in data workflows and analytics functions
  • Construct customer specific realtime (batched streaming) and offline (MR, ETL, etc) demonstration workflows
  • Iteratively build demonstration test beds incorporating different technologies and data sources as needed


  • Proficient in Linux (CLI level operations)
  • Significant experience with data integration, data ingestion, and data transformation required.
  • Deep knowledge in data mining, machine learning, audio and video processing, and information retrieval.
  • Data modelling, visualization, predictive and prescriptive analytics
  • Grasp of object-oriented design, computer science, and data processing best practices
  • Programming and scripting experience, ideally in Python or Java
  • Data modeling experience processing structured and unstructured data using modern languages and tools such as R, Scala, RStudio, SPSS
  • Big Data and data warehouse products and services such as Hadoop, MapReduce, HiveQL, Apache Spark, other NoSQL and SQL tools.
  • Experience using Teradata, Oracle, SAP, and other ingestion and transformation tools from major providers
  • Experience in machine learning solutions: Tensorflow, Computer Vision
  • Excellent interpersonal and communications skills, verbal and written.


  • Technical familiarity with Docker, Kubernetes, and related container and orchestration tools
  • Understanding and working knowledge of cloud infrastructure and tools such as AWS IoT, AWS Kenesis, AWS Lambda, Azure IoT Event Hubs, Azure Stream Processing, IBM Watson IoT and Bluemix
  • Experience in micro-service applications
  • Experience with message brokering systems (MQTT, HTTP, AMQP, RabbitMQ, Kafka protocols)
  • Knowledge of servers, storage systems, industrial devices (e.g. IoT sensors, gateways), and other common enterprise and hyperscale hardware


  • BSEE/MSEE or related discipline or experience

Equal Opportunity Employer Minorities/Women/Protected Veterans/Disabled

Req # 1665

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