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    Big Data Architect - Chicago, United States - NavitsPartners

    NavitsPartners
    NavitsPartners Chicago, United States

    3 weeks ago

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    Description
    Job Description

    Job Description


    Position:
    Big Data Architect

    Location:
    Chicago, IL

    Duration:

    1 Year

    Job Description:


    We are seeking a highly skilled Principal Consultant-Senior Data Engineer SRE (Site Reliability Engineer) to join our team in Chicago, IL.

    In this role, you will be responsible for designing, building, securing, and maintaining data infrastructure on Google Cloud Platform (GCP).

    You will play a critical role in optimizing data pipelines, ensuring data integrity and consistency, enhancing system resiliency, and maintaining and improving data security.


    Responsibilities:
    Automate data tasks on GCP to streamline data operations and improve efficiency.
    Collaborate with data domain owners, data scientists, and stakeholders to ensure effective consumption of data on GCP.
    Design, build, secure, and maintain data infrastructure, including data pipelines, databases, data warehouses, and data processing platforms on GCP.

    Measure and monitor the quality of data on GCP data platforms and implement robust monitoring and alerting systems to proactively identify and resolve issues.

    Develop automation scripts and tools to streamline data operations and make them scalable.
    Optimize data systems to ensure efficient data processing, reduce latency, and improve overall system performance.
    Collaborate with data and infrastructure teams to forecast data growth and plan for future capacity requirements.
    Ensure data security and compliance with data protection regulations, implementing best practices for data access controls and encryption.
    Collaborate with data engineers, data scientists, and software engineers to troubleshoot issues and support data-driven initiatives.
    Continuously assess and improve data infrastructure and data processes to enhance reliability, efficiency, and performance.
    Maintain clear and up-to-date documentation related to data systems, configurations, and standard operating procedures.

    Qualifications:

    Minimum Qualifications / Skills:
    Bachelor's or master's degree in computer science, Software Engineering, Data Science, or related field, or equivalent practical experience.

    Preferred Qualifications/ Skills:


    Proficiency in data technologies such as relational databases, data warehousing, big data platforms (e.g., Hadoop, Spark), data streaming (e.g., Kafka), and cloud services (e.g., AWS, GCP, Azure).

    Strong programming skills in languages like Python, Java, or Scala, with experience in automation and scripting.
    Experience with containerization and orchestration tools like Docker and Kubernetes.
    Experience with data governance, data security, and compliance best practices on GCP.
    Solid understanding of software development methodologies and best practices, including version control (e.g., Git) and CI/CD pipelines.
    Strong background in cloud computing and data-intensive applications and services, with a focus on Google Cloud Platform.
    Experience with data quality assurance and testing on GCP.
    Proficiency with GCP data services (BigQuery, Dataflow, Data Fusion, Dataproc, Cloud Composer, Pub/Sub, Google Cloud Storage).
    Strong understanding of logging and monitoring using tools such as Cloud Logging, ELK Stack, AppDynamics, New Relic, Splunk, etc.
    Knowledge of AI and client tools is a plus.
    Google Associate Cloud Engineer or Data Engineer certification is a plus.
    Experience in data engineering or data science on GCP.
    ChatGPT can make mistakes

    #J-18808-Ljbffr
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