Data Engineer - Phoenix, United States - TalentAmp

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    Description
    TalentAmp is currently looking for Data Engineer II for one of our clients in Phoenix area.

    You will work in close collaboration with operations, subject matter experts, data scientists, and software engineers to develop advanced, highly automated data products.

    You will be a champion of DataOps, and agile practices; actively participating in project teams to drive value.

    Lead cross-functional teams for innovative analytic solutions.
    Design and review diverse data pipelines, mentoring junior members.
    Provide thought leadership and actively engage in R&D initiatives.
    Utilize cloud technologies and DevOps/DataOps best practices for high-quality code.
    Identify and implement code optimization opportunities, leveraging external expertise.
    Seek new opportunities for skill enhancement and research latest technologies.


    Requirements:
    Bachelor's degree in engineering, computer science, analytical field (Statistics, Mathematics, etc.) or related discipline with five (5) years of relevant work experience, or
    Master's in engineering, computer science, analytical field (Statistics, Mathematics, etc.) or related discipline with three (3) years of relevant work experience, or
    Ph.
    D.

    in engineering, computer science, analytical field (Statistics, Mathematics, etc.) or related discipline with one (1) year of relevant work experience.


    Strong experience in at least three areas:
    Knowledgeable Practitioner of SQL development with experience designing high-quality, production SQL codebases.
    Knowledgeable Practitioner of Python development with experience designing high-quality, production Python codebases.
    Knowledgeable Practitioner in data engineering, software engineering, and ML systems architecture.
    Knowledgeable Practitioner of data modeling.
    Experience applying software development best practices in data engineering projects, including Version Control, P.R.

    Based Development, Schema Change Control, CI/CD, Deployment Automation, Test-Driven Development/Test Automation, Shift left on Security, Loosely Coupled Architectures, Monitoring, Proactive Notifications using Python and SQL.

    Data science experience wrangling data, model selection, model training, modeling validation, e.g., Operational Readiness Evaluator and Model Development and Assessment Framework, and deployment at scale.

    If you meet these qualifications and are interested in this opportunity, please apply with your updated resume.

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