Senior Data Architect (GenAI)

A leading enterprise insurance firm within a highly regulated industry is seeking an experienced Senior Data Architect (GenAI) with deep expertise in data architecture, cloud platforms, and AI/ML technologies to drive next-generation data and AI transformation initiatives.

Key responsibilities:

• Define and drive enterprise-wide AI data architecture strategies, standards, and best practices to support AI and Generative AI initiatives.

• Design and implement end-to-end data architectures for AI/ML and Generative AI use cases, including data ingestion, orchestration, processing, storage, model integration, and consumption leveraging modern Azure services such as Azure Data Factory and Azure Databricks.

• Develop and maintain architecture roadmaps, target-state architectures, and technology blueprints for AI and analytics platforms, ensuring alignment with enterprise technology and business strategies.

• Lead the design and implementation of scalable, secure, and high-performance data pipelines using Azure Data Factory, Azure Databricks, Spark, and Delta Lake technologies, ensuring data quality, reliability, observability, and SLA adherence.

• Architect and optimize modern lakehouse and data platform solutions, supporting batch, streaming, and real-time analytics workloads.

• Provide technical leadership in AI data platform design, including support for Large Language Model (LLM) integration, Retrieval-Augmented Generation (RAG), vector search, semantic data models, and agentic AI workflows.

• Support domain-specific use cases such as policy analysis, claims processing, fraud detection, underwriting insights, customer service automation, and predictive analytics.

• Lead performance tuning, scalability optimization, and troubleshooting across data pipelines, cloud platforms, and AI model deployments, ensuring resilient and sustainable solutions.

• Collaborate with enterprise architecture, engineering, security, governance, and business teams to translate requirements into robust, scalable, and future-ready solutions.

• Participate in architecture governance forums, design reviews, solution assessments, and technology evaluations, ensuring alignment with enterprise standards, security requirements, and regulatory obligations.

• Establish and enforce data governance, metadata management, security, and compliance frameworks, ensuring adherence to privacy regulations and responsible AI practices.

• Drive continuous improvement, innovation, and adoption of emerging cloud, data, and AI technologies, contributing reusable architecture patterns, accelerators, and best practices.

• Mentor and provide technical guidance to engineering and architecture teams, fostering engineering excellence and architectural consistency across initiatives.

Candidate profile:

• Degree in Computer Science, Information Technology, Engineering, or a related discipline.

• Minimum 10 years of experience in Data Architecture, Data Engineering, or related disciplines within large and complex enterprise environments.

• At least 4 years of hands-on experience designing and implementing AI/ML and Generative AI data architectures at enterprise scale.

• Strong expertise in cloud platforms (Azure preferred) and modern data ecosystem design.

• Hands-on experience designing and implementing enterprise data platforms using Azure Databricks, Spark, Delta Lake, Medallion Architecture, Azure Data Factory, Azure Data Lake Storage, and related Azure analytics services.

• Strong understanding of modern lakehouse architectures, data modeling, metadata management, data governance, and performance optimization techniques.

• Experience designing large-scale data ingestion, transformation, orchestration, and integration solutions using Azure Data Factory and Databricks.

• Proficiency in data engineering and analytical technologies such as Python, SQL, Spark, machine learning frameworks, and data processing tools.

• Hands-on experience with Generative AI technologies, including:

  • LLM integration and prompt engineering
  • Retrieval-Augmented Generation (RAG)
  • Vector databases and semantic search
  • AI model governance and lifecycle management
  • Emerging paradigms such as agentic AI frameworks and AI orchestration

• Experience working with MLOps, DataOps, and modern CI/CD practices for AI and data platform delivery.

• Experience operating within regulated industries such as insurance, financial services, healthcare, or similar sectors, with strong understanding of data privacy, governance, security, and compliance requirements.

• Strong experience in defining architecture strategies, standards, roadmaps, and target-state architectures, with the ability to influence senior stakeholders and technology leadership.

• Proven ability to work in complex, fast-paced environments, manage multiple priorities, and deliver high-impact business outcomes.

• Excellent communication, presentation, and stakeholder management skills, with demonstrated ability to collaborate effectively across business and technology teams.

About the organization:

A large-scale, forward-looking enterprise undergoing significant data and AI transformation, focused on leveraging advanced analytics and emerging AI technologies to drive business innovation, enhance customer experiences, and optimize risk and operational outcomes.

The organization operates in a regulated industry environment, placing strong emphasis on governance, security, and ethical AI adoption, while fostering a culture of technology innovation, collaboration, and continuous improvement.

Keywords:

AI Data Architect, Data Architecture, Generative AI, LLM, RAG, Agentic AI, Insurance Analytics, Claims Automation, Fraud Detection, Data Platform, Cloud Architecture, Azure, Machine Learning, Digital Transformation