Jobs

    Data Architect - Singapur, Singapore - Infosys Singapore & Australia

    Infosys Singapore & Australia
    Infosys Singapore & Australia Singapur, Singapore

    11 hours ago

    Default job background
    Full time
    Description

    We are looking for a highly experienced and skilled Data Architect to join our team. The ideal candidate will have 12-15 years of experience in architecting solutions of data engineering, focusing on ELT and PySpark/Hadoop workloads. In addition to strong solution and delivery skills, the ideal candidate will also have a view on business growth and managing stakeholders.

    Responsibilities:

    • Design and implement high-performance, scalable, and secure data architectures.
    • Work with business stakeholders to understand their data needs and translate them into technical requirements.
    • Design and develop data pipelines and workflows using ELT principles and PySpark/Hadoop
    • Optimize data pipelines and workflows for performance and efficiency
    • Work with data scientists and engineers to ensure that data is accessible and usable for analytics and machine learning
    • Implement data governance and security best practices
    • Manage and mentor data engineers
    • Contribute to the overall data engineering strategy and roadmap

    Requirements

    Qualifications:

    • 12-15 years of experience in data engineering, with a focus on ELT and PySpark/Hadoop workloads
    • Strong experience in designing and implementing high-performance, scalable, and secure data architectures.
    • Experience with data governance and security best practices
    • Experience in managing and mentoring data engineers
    • Excellent communication and interpersonal skills
    • Ability to work independently and as part of a team
    • Strong problem-solving and analytical skills

    Desired Skills:

    • Experience with cloud computing platforms such as AWS, Azure, or GCP
    • Experience with big data technologies such as Spark, Hadoop, Hive, and Kafka
    • Experience with data warehousing and data lakes
    • Experience with DevOps and MLOps practices
    • Experience with data science and machine learning, streaming data processing
    • Experience with real-time analytics, data visualization and reporting tools

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