Senior Data Engineer

YO AI Labs

  • Glendale, California
  • 24 days ago
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    Skills

    • Application Programming Interface (API)unmatched
    • Best Practicesunmatched
    • Cloud Computingunmatched
    • Data Managementunmatched
    • Data Modelingunmatched
    • Data Processingunmatched
    • Data Qualityunmatched
    • Data Setsunmatched
    • Database Technologyunmatched
    • Distributed Computingunmatched
    • Documentationunmatched
    • Engineeringunmatched
    • GraphQLunmatched
    • OLAP (OnLine Analytical Processing)unmatched
    • Operations Managementunmatched
    • Parallel Computingunmatched
    • Production Systemsunmatched
    • Programming Languagesunmatched
    • Python Programming/Scripting Languageunmatched
    • Service Level Agreement (SLA)unmatched
    • Snowflake Schemaunmatched
    • Software Engineeringunmatched
    • Transaction Processing/Managementunmatched

    Description

    Job Description

    • Job title: Senior Data Engineer
    • Experience: 5-20 Years
    • Location: Glendale, USA
    • Job Type: Contract, On-site


    Must Haves:

    • Candidates must be willing to work on W2, no C2C. 
    • 5+ years of data engineering experience specifically developing large-scale data pipelines.
    • Databricks and Python expertise.


    Qualifications:

    • 5+ years of data engineering experience developing large data pipelines
    • Proficiency in at least one major programming language.
    • Expertise on databricks and Python.
    • Hands-on production environment experience with distributed processing systems such as Spark
    • Hands-on production experience with data pipeline orchestration systems such as Airflow for creating and maintaining data pipelines
    • Experience with at least one major Massively Parallel Processing (MPP) or cloud database technology (Snowflake, Databricks, Big Query).
    • Experience in developing APIs with GraphQL
    • Advanced understanding of OLTP vs OLAP environment.
    • Strong background in at least one of the following: distributed data processing or software engineering of data services, or data modeling



    Key Responsibilities:

    • Contribute to maintaining, updating, and expanding existing Core Data platform data pipelines.
    • Build and maintain APIs to expose data to downstream applications.
    • Develop real-time streaming data pipelines.
    • Tech stack includes Airflow, Spark, Databricks, Delta Lake, and Snowflake.
    • Collaborate with product managers, architects, and other engineers to drive the success of the Core Data platform.
    • Contribute to developing and documenting both internal and external standards and best practices for pipeline configurations, naming conventions, and more.
    • Ensure high operational efficiency and quality of the Core Data platform datasets to ensure our solutions meet SLAs and project reliability and accuracy to all our stakeholders.

    Numbers & Facts

    LocationGlendale, California

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