Data Architect MIS

• Provide thought leadership, strategic insight, and clear communication on Data Architecture and implementation for complex problems. 
• Design, construct, install, test, and maintain highly scalable data management systems. Ensure systems meet business requirements and industry best practices. Design and implement effective database solutions and models using Azure Data architectures and frameworks (Databricks, Azure Data Factory and Azure databases or Fabric implementation). Assess database implementation procedures to ensure they comply with internal and external regulations. Ensure these solutions are scalable, reliable, and secure. 
• Develop data design and architecture documentation for the management and executive teams. Create logical and physical data models using best practices to ensure high data quality and reduced redundancy. 
• Develop strategies for data integrations, retention, archival/purge along with DR.  
• Selects and implements database management systems that meet the organization’s needs by defining data schemas, optimizing data storage, and establishing data access controls and security measures 
• Defines and implements the long-term technology strategy and innovations roadmaps across analytics, data engineering, and data platforms 
• Designs and implements processes for the ETL process from various sources into the organization’s data systems 
• Translates high-level business requirements into data models and appropriate metadata, test data, and data quality standards 
• Simplifies the existing data architecture, delivering reusable services and cost-saving opportunities in line with the policies and standards of the company 
• Leads and participates in the peer review and quality assurance of project architectural artifacts across the EA group through governance forums 
• Defines and manages standards, guidelines, and processes to ensure data quality 
• Collaborate with IT teams, management, data analysts and data scientists to determine future needs and requirements. Facilitate collaboration across multiple teams. 
• Work with Data Governance and Security teams to help develop and implement data standards, ensuring privacy regulations and security are met. 
• Work closely with the AI/Data Analytics teams to understand their needs and challenges. Leverage your expertise to work with to provide data-driven solutions that address these issues. 
• Work closely with IoT implementation teams to understand the time series based data and implement solutions that can fit the long term picture. 
• Stay updated with the latest trends and advancements in the data space including databases (Wide range), data science, AIML, GenAI and cloud data computing. 
• Evaluates and recommends emerging technologies for data management, storage, and analytics  

• A master’s degree in computer science, Statistics, Mathematics, or a related field is required. A bachelor’s degree with significant relevant experience would suffice. 
• 10+ years working in the IT industry with 8+ years of experience in data related architecture/design and implementations is needed. 
• Excellent analytical and problem-solving skills. 
• Experience with Microsoft Azure and its suite of data tools is crucial. This includes but is not limited to Azure databases, Azure Machine Learning, Azure Data Services, Azure Databricks, and Azure Synapse Analytics along with On Prem implementations of SQL Server etc. is needed. Also, any experience across a multi cloud environment is preferred. 
• Should have coded in .NET or Java prior to becoming Architect. Knowledge of C#, Python, or other data processing languages. 
• Experience with SQL, Oracle, NoSQL databases and Data Fabric architectures. 
• Familiarity with big data technologies such as Hadoop, Hive and Spark 
• Experience with machine learning frameworks like PyTorch, Tensorflow or Scikit-learn. 
• Knowledge of AI and Data Analytics principles is preferred. 
• Knowledge of data visualization tools (Power BI, Tableau, etc.)  is preferred. 
• Strong communication skills to effectively collaborate with team members and stakeholders. 
• Ability to translate complex findings into a compelling narrative for non-technical stakeholders. 
• Certifications like Microsoft Certified: Azure Data Scientist Associate, Data Engineer or Microsoft Certified: Azure AI Engineer Associate will be preferred. 

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