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    Data Engineer - Richmond, United States - Insight Global

    Insight Global
    Insight Global Richmond, United States

    4 weeks ago

    Insight Global background
    Description

    Job Description

    Job Description

    Must Haves:

    • Minimum 5 years working experience as Data Analyst
    • Strong understanding of Data warehousing (Dimensional Modeling, ETL etc.) and RDBMS concepts
    • Minimum 5 years working experience in SQL, Stored Procedures and Table Design
    • Minimum 5 years working experience in SQL Query optimization and ETL Data loading Performance
    • Minimum 5 years working experience in Snowflake Cloud Data warehouse
    • Minimum 5 years working experience in R/Python and Spark
    • Minimum 2 years working experience in shell scripting

    Plusses:

    • Experience with Talend ETL tool is a big plus
    • Experience with cloud technologies(AWS, Azure, GCP) is big plus
    • Experience in real time streaming technologies is plus
    • Experience deploying machine learning models and automating processes in production is a plus
    • Experience as a Data Engineer in Hadoop Platforms on components like HIVE, KAFKA, NiFi, Spark etc is a big plus.

    Day to Day:

    • Analyzing large data sets to identify trends, patterns, and insights.
    • Design, Develop and maintain secure, consistent and reliable ETL solutions supporting critical business processes across the various Business Units.
    • Ensuring data solutions are compliant with enterprise security standards.
    • Developing and performing tests to validate data flows and prepare ETL processes to meet complex business requirements.
    • Coordinating with various teams to ensure jobs designed and developed meet support standards and best practices before migration into the production environment.
    • Defining and capturing metadata and rules associated with ETL processes.
    • Work in complex multi-platform environments on multiple project assignments.
    • Uses strategies such as Indexing and partitioning to fine tune the data warehouse and big data environments to improve the query response time and scalability.
    • Define and capture metadata and rules associated with ETL processes.
    • Effectively communicate the findings to both technical and non-technical audiences.
    • Assist production support team in providing resolutions to production job failures, data issues and performance tuning.
    • ETL Development and Process Support, may require weekend/off business hours work.
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