Cloud Data Architect - ETL/Data Warehousing

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 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.
 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 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.
 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.
 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,