Data Architect

Roles & Responsibilities:

• Design and develop enterprise-scale cloud data platforms.
• Lead the design and development of GenAI and Agentic AI solutions.
• Understand business requirements and translate them into scalable technical solutions.
• Drive architecture discussions and technical strategy with stakeholders.
• Design and implement data solutions using AWS Databricks PySpark ETL and DLT.
• Define architecture standards coding standards and best practices.
• Collaborate with Product Managers Engineering Managers Scrum Masters and Technical Leads.
• Lead technical design reviews and solution walkthroughs with clients.
• Provide technical leadership mentoring and guidance to engineering teams.
• Resolve complex technical challenges.
• Ensure enterprise security governance and data management standards are followed.
• Deliver scalable secure and high-performance data solutions.
• Support sprint and milestone commitments.
• Work closely with cross-functional teams to deliver AI-driven products and platforms.

Required Skills:

• 10 years of experience in Data Engineering/Data Architecture.
• Strong hands-on experience with AWS Databricks and PySpark.
• Expertise in ETL development and Delta Live Tables (DLT).
• Strong knowledge of modern Data Lakehouse architecture.
• Experience in data modeling orchestration and pipeline optimization.
• Experience designing and implementing enterprise-scale cloud data platforms.
• Strong experience in Generative AI LLMs AI Agents and orchestration frameworks.
• Good understanding of AI/ML architecture integration security and scalability.
• Excellent communication and stakeholder management skills.
• Experience leading architecture discussions and client interactions.
• Experience working in Agile environments.
• Experience mentoring technical teams.
• AWS and Databricks Architecture experience.
• TOGAF Certification is preferred.
• Experience working with banking clients such as JPMC Citi Wells Fargo or similar is preferred.