Cloud Data Architect

4 weeks ago

Mumbai, India EDGESOFT Full time

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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