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    Lead Data Engineer - Rockville, United States - Optomi

    Optomi
    Optomi Rockville, United States

    2 weeks ago

    Default job background
    Technology / Internet
    Description

    Lead Data Engineer | Remote

    Optomi, in partnership with a global leader in the financial services industry, is seeking a Lead Data Engineer to join their team This candidate will be responsible for designing, ingesting, storing, validating and disseminating data in a consumable format, for business intelligence teams and data analysts to get deeper business insight from the data.

    What the right candidate will have:

    • 7+ years of strong experience in Java or Scala
    • 7+ years of experience in ETL projects
    • 5+ years of experience in big data projects
    • 3+ years of experience with API development (REST API's)
    • Strong experience in big data technologies like AWS EMR, AWS EKS, Apache Spark
    • Strong experience with technologies like AWS Dynamo DB, AWS Lambda
    • Strong experience in processing with JSON and CSV files
    • Must be able to write complex SQL queries
    • Experience in performance tuning and optimization
    • Familiar with columnar storage formats (ORC, Parquet) and various compression techniques
    • Experience in writing Unix shell scripts
    • Unit testing using JUnit or ScalaTest
    • Git/Maven/Gradle
    • Code Reviews
    • Experience with CI/CD pipelines
    • Believes in Scrum/Agile, and has deep experience delivering software when working on teams that use Scrum/Agile methodology
    • Strong and creative analytical and problem-solving skills

    Responsibilities of the right candidate:

    • Understand complex business requirements
    • Design and develop ETL pipeline for collecting, validating and transforming data according to the specification
    • Develop automated unit tests, functional tests and performance tests.
    • Maintain optimal data pipeline architecture
    • Design ETL jobs for optimal execution in AWS cloud environment
    • Reduce processing time and cost of ETL workloads
    • Lead peer reviews and design/code review meetings
    • Provide support for production support operations team
    • Implement data quality checks.
    • Identify areas where machine learning can be used to identify data anomalies
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