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    Cloud Data Architect - Mumbai, India - EDGESOFT

    EDGESOFT
    EDGESOFT Mumbai, India

    43 minutes ago

    Default job background
    permanent Technology / Internet
    Description

    Job Description :
    Cloud Data Architect - Data Warehousing/Data Lake for Enterprise


    Position Overview :


    We are seeking a talented and experienced Cloud Data Architect to lead the design and implementation of a robust, scalable, and efficient cloud-based data warehousing and data lake solution for our enterprise.

    As a Cloud Data Architect, you will play a pivotal role in shaping the data architecture strategy, ensuring optimal data management, integration, and analytics capabilities to support the organization's data-driven decision-making processes.


    Key Responsibilities :

    Data Architecture Strategy :

    • Define the overall data architecture strategy, considering the organization's data requirements, scalability, security, and performance.
    • Collaborate with stakeholders to understand business needs and translate them into technical requirements.

    Cloud Data Platform Design :

    • Design and architect the cloudbased data warehousing and data lake solutions, selecting appropriate technologies and services based on business needs and best practices.
    • Create blueprints and data models that support efficient data storage, processing, and analytics.
    • Data Integration and

    ETL :

    • Develop strategies for data integration, transformation, and ETL processes across various sources and formats.
    • Implement data pipelines to move, transform, and cleanse data from source systems to the data warehouse and data lake.

    Scalability and Performance :

    • Design solutions that can scale seamlessly to accommodate increasing data volume and user demands.
    • Optimize data storage and query performance to ensure efficient data retrieval and analysis.

    Security and Compliance :

    • Implement robust security measures to ensure data privacy and compliance with industry regulations and standards.
    • Define access controls and data encryption mechanisms to protect sensitive information.

    Data Governance and Quality :

    • Establish data governance practices, including data cataloging, metadata management, and data lineage tracking.
    • Monitor and maintain data quality standards to ensure accuracy and reliability of the data.

    Collaboration and Leadership :

    • Collaborate closely with crossfunctional teams, including data engineers, data scientists, analysts, and business stakeholders, to align technical solutions with business objectives.
    • Provide technical leadership and guidance to the data engineering team.

    Cloud Platform Expertise :

    • Utilize cloud services and platforms such as AWS, Azure, or Google Cloud to build and manage the data architecture.
    • Stay uptodate with the latest cloud technologies and services relevant to data management and analytics.

    Performance Monitoring and Optimization :

    • Implement monitoring and alerting mechanisms to proactively identify performance bottlenecks and issues.
    • Continuously optimize data processing workflows and architecture for improved efficiency.

    Required Qualifications :

    • Bachelor's or Master's degree in Computer Science, Information Systems, or a related field (or equivalent practical experience).
    • Proven experience (8+ years) as a Data Architect, Cloud Data Engineer, or similar role, focusing on designing and implementing cloudbased data warehousing and data lake solutions for enterprisescale applications.
    • Expertise in cloud platforms such as AWS, Azure, or Google Cloud, with handson experience in cloud data services (e.g., AWS Redshift, Azure Synapse Analytics, Google BigQuery).
    • Proficiency in data modeling, data integration, ETL processes, and data transformation.
    • Strong understanding of data governance, data quality, and data security practices.
    • Experience with SQL, NoSQL databases, and distributed data processing frameworks (e.g., Hadoop, Spark).
    • Excellent knowledge of data warehousing concepts, data architecture patterns, and best practices.
    • Familiarity with data visualization and analytics tools (e.g., Tableau, Power BI, Quicksight).
    • Strong communication skills and the ability to work collaboratively in crossfunctional teams.
    • Problemsolving mindset and the ability to troubleshoot complex technical challenges.

    Preferred Qualifications :

    • Professional certifications related to cloud platforms, data architecture, or data engineering.
    • Experience with containerization and orchestration tools (e.g., Docker, Kubernetes).
    • Knowledge of machine learning and AI technologies for advanced analytics.
    • Previous involvement in migrating onpremises data solutions to the cloud.
    • Contributions to relevant opensource projects or technical publications.
    )
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