EDGESOFT
Location
Mumbai | India
Job 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 : 1. 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. 2. Cloud Data Platform Design : - Design and architect the cloud-based 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. 3. 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. 4. 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. 5. 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. 6. 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. 7. Collaboration and Leadership : - Collaborate closely with cross-functional 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. 8. Cloud Platform Expertise : - Utilize cloud services and platforms such as AWS, Azure, or Google Cloud to build and manage the data architecture. - Stay up-to-date with the latest cloud technologies and services relevant to data management and analytics. 9. 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 cloud-based data warehousing and data lake solutions for enterprise-scale applications. - Expertise in cloud platforms such as AWS, Azure, or Google Cloud, with hands-on 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 cross-functional teams. - Problem-solving 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 on-premises data solutions to the cloud. - Contributions to relevant open-source projects or technical publications. (ref:hirist.tech)
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