Open Opportunity

Data Engineer

Covina, CA

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Openings with a very well established company in Covina, CA. They did over $140M in revenue last year, clearing $40M before taxes. Recently brought in a new rockstar CTO who I’ve worked with for 15 years since we’d worked together at Overture/Yahoo! back in the early 2000s. He’s basically building out a Tech start-up within this company taking them from old mainframe systems to state of the art, React front end, GoLang backend, Google Cloud as well as building out a brand new state of the art 10,000 SF offices.

Summary Objective

As a data engineer, you will help lead the effort of transforming the data systems. You will work with a diverse set of data sources and systems, and provide the design, and definition of a new data platform.

Essential Functions

  • Data architecture, development platform and tools for collection, processing, and storage/retrieval of petabyte-scale data sets..
  • Develop and implement core data pipeline components utilizing Google Cloud Platform tools and technologies.
  • Develop interfaces to internal and external systems based on standard transports and formats.
  • Develop and evolve data models, layouts, and access patterns for all data collections.
  • Provide proactive support for data platform pipelines and components and respond to ad-hoc requests.

Position Requirements

  • Bachelor’s degree in Computer Science or equivalent, or relevant experience.
  • 4-5 years of design and development of data pipelines and/or data intensive applications encompassing the following areas:
    • Batch and real-time delivery of data across multiple technologies (pub-sub, APIs, log processing).
    • Developing and deploying modules inside data processing frameworks such as Spark and MapReduce.
    • Experience with each of the following technologies: relational databases, NoSql databases, data warehousing.
    • Building data pipelines using standard workflow tools and concepts.
    • Proficiency with SQL and Java, Scala, or Python.
  • Experience with building and deploying data applications on any Cloud infrastructure (Google Cloud Platform, Amazon Web Services, Azure).
  • Robust knowledge of data warehousing technology and concepts.
  • Experience with building data processing components using standard big data technology stack (or equivalent): MapReduce, Spark, Spark SQL, Spark Streaming, Hive, Pig, Impala, HBase
  • Experience interacting with and/or administering any of the following relational databases: PostgreSQL, MySQL, Oracle, SQL Server.
  • Experience with one of the following pub/sub technologies: Google Cloud Pub/Sub, Kafka, Kinesis.
  • Cloud platform certification (big data related) is a plus.
  • Deep understanding of distributed environments and resource management.
  • Strong communication skills (verbal and written) and ability to communicate with both business and technical teams.