Lead Data Architect--Need Locals

Hi All,

Good morning,

We have an urgent position for the below mentioned requirement.

• Lead Data Architect will lead the overall effort on future state architecture roadmap, business alignment, and overall data strategy and end to end data lifecycle including data quality, data governance, data modeling, etc.
• Establish and enforce data governance policies, standards, and procedures to ensure data quality, integrity, security, and compliance.
• Define data ownership, stewardship, and lineage processes.
• Design data architectures that are performant, scalable, and resilient. Identify and address performance bottlenecks and optimize data storage and retrieval processes.
• Solid experience in Azure / other public clouds (Azure preferred) and cloud-based data platforms such as Databricks and Snowflake - involving various data services, cost / performance trade-offs, architecture patterns / choices, etc.
• Define and implement data security measures, including access controls, encryption, and data masking, to protect sensitive information and ensure compliance with relevant regulations.
• Experience involving Azure Fabric strongly required.
• Effective communicator with ability to communicate complex techno-functional aspects to various stakeholders including business stakeholders
• Prior experience in Mortgage/banking industry require.

• Bachelor's degree in computer science, Engineering, Mathematics, or a related field. 12 to 15 years of overall IT experience with minimum 10 years in data and analytics space 5+ years of experience in Data Advisory, Data Strategy, ADF and defining architecture roadmap (at least 2 full implementation experience from strategizing the architecture to roll-out) Proven experience in designing and implementing data solutions on cloud platforms like AWS, Azure, Google Cloud Platform, Snowflake, etc. Deep understanding of various data modeling techniques (e.g., relational, dimensional, data vault).
• Strong expertise in database technologies (both SQL and NoSQL) and data warehousing principles.
• Experience with data integration tools and techniques (ETL/ELT).
• Solid understanding of data governance, data quality, and data security best practices.
• Excellent problem-solving, analytical, and critical-thinking skills. Strong communication, presentation, and interpersonal skills with the ability to influence stakeholders.
• Demonstrated ability to lead and mentor technical teams.
• Familiarity with data science workflows and machine learning concepts is a plus.

• Relevant certifications in data architecture or cloud technologies.
• Experience in [mention specific industry experience if relevant].
• Knowledge of data mesh or other modern data architecture paradigms.