Data Architect

As a Data Architect at Qzensys Solutions, you will be responsible for designing and optimizing data warehouse and data lake architectures with a focus on Flexcube 8+. Your daily tasks will include defining data models, implementing ETL/ELT pipelines, setting data standards, and collaborating with stakeholders to translate requirements into scalable data solutions. Additionally, you will establish data governance practices, troubleshoot data issues, and ensure data quality, security, and compliance. Key Responsibilities: - Design and optimize data warehouse and data lake architectures, ensuring robust integration with Flexcube and other core banking systems. - Define data models and implement ETL/ELT pipelines. - Set data standards and collaborate with stakeholders to translate requirements into scalable data solutions. - Establish data governance practices, troubleshoot data issues, and ensure data quality, security, and compliance. Qualifications: - Strong experience in Data Architecture and designing scalable data warehouse/data lake solutions, preferably in financial services or banking environments. - Hands-on skills in Data Modeling and Data Warehousing, including dimensional modeling and optimization for analytics and reporting. - Proficiency in ETL processes and tools, including building, orchestrating, and monitoring data integration pipelines. - Experience implementing Data Governance practices, including data quality, metadata management, data lineage, and access controls. - Proven Flexcube 8+ experience, including integration patterns, data structures, and best practices for core banking data management. - Strong SQL skills and familiarity with modern cloud data platforms or on-premise data warehouse technologies. - Ability to work independently in a remote, part-time contract setting while managing multiple priorities and deadlines. - Excellent communication skills to collaborate with cross-functional teams and explain complex data concepts to non-technical stakeholders. - Bachelors degree in Computer Science, Information Systems, Engineering, or related field, or equivalent practical experience. - Relevant certifications in data architecture, cloud platforms, or data governance are a plus. As a Data Architect at Qzensys Solutions, you will be responsible for designing and optimizing data warehouse and data lake architectures with a focus on Flexcube 8+. Your daily tasks will include defining data models, implementing ETL/ELT pipelines, setting data standards, and collaborating with stakeholders to translate requirements into scalable data solutions. Additionally, you will establish data governance practices, troubleshoot data issues, and ensure data quality, security, and compliance. Key Responsibilities: - Design and optimize data warehouse and data lake architectures, ensuring robust integration with Flexcube and other core banking systems. - Define data models and implement ETL/ELT pipelines. - Set data standards and collaborate with stakeholders to translate requirements into scalable data solutions. - Establish data governance practices, troubleshoot data issues, and ensure data quality, security, and compliance. Qualifications: - Strong experience in Data Architecture and designing scalable data warehouse/data lake solutions, preferably in financial services or banking environments. - Hands-on skills in Data Modeling and Data Warehousing, including dimensional modeling and optimization for analytics and reporting. - Proficiency in ETL processes and tools, including building, orchestrating, and monitoring data integration pipelines. - Experience implementing Data Governance practices, including data quality, metadata management, data lineage, and access controls. - Proven Flexcube 8+ experience, including integration patterns, data structures, and best practices for core banking data management. - Strong SQL skills and familiarity with modern cloud data platforms or on-premise data warehouse technologies. - Ability to work independently in a remote, part-time contract setting while managing multiple priorities and deadlines. - Excellent communication skills to collaborate with cross-functional teams and explain complex data concepts to non-technical stakeholders. - Bachelors degree in Computer Science, Information Systems, Engineering, or related field, or equivalent practical experience. - Relevant certifications in data architecture, cloud platforms, or data governance are a plus.