Prudential’s purpose is to be partners for every life and protectors for every future. Our purpose encourages everything we do by creating a culture in which diversity is celebrated and inclusion assured, for our people, customers, and partners. We provide a platform for our people to do their best work and make an impact to the business, and we support our people’s career ambitions. We pledge to make Prudential a place where you can Connect, Grow, and Succeed.

Prudential is seeking an accomplished Data & AI Solutions Architect to design, lead, and deliver enterprise-grade data and AI solutions across the organization, with a strong emphasis on the Insurance domain. The ideal candidate combines deep technical mastery of modern data and AI platforms — including cloud-native architectures, ETL/ELT engineering, and Agentic AI — with strong business acumen across insurance operations, actuarial processes, and corporate functions like Finance, HR, Risk, Sustainability. This role requires a consulting mindset, the ability to engage confidently with senior business stakeholders, and the technical credibility to architect solutions that are scalable, governed, responsibly engineered, and production-ready.

• Architect end-to-end data and AI solutions spanning data ingestion, data modeling, data warehousing, machine learning pipelines, and MLOps, ensuring scalability, security, and performance.

• Lead the design and implementation of enterprise data platforms on Databricks, including Unity Catalog-based governance, access control, lineage, and data cataloguing.

• Define target-state data architectures, enterprise data products, conceptual/logical/physical data models, and UML-based design artifacts that translate business requirements into robust technical solutions.

• Design and optimize data pipelines using modern ETL/ELT tools such as DBT, PySpark, Azure Data Factory (ADF), Cloud Composer, and Apache Airflow, ensuring data quality, reliability, and operational efficiency at scale.

• At ease with SQL and NoSQL ecosystems and governance platforms like Informatica

• Architect and implement Agentic AI solutions and broader AI Stack capabilities, leveraging platforms such as Azure AI Foundry, to deliver autonomous, HITL and assistive AI use cases for the business.

• Champion responsible AI practices across the AI development lifecycle (AI-SDLC), including red teaming and evaluation frameworks, to ensure AI solutions are safe, robust, and fit for production.

• Lead the design and delivery of cloud-based data and AI solutions, with hands-on architecture and implementation experience across Azure and GCP.

• Build and present compelling business cases, architecture decks, and executive-level communications using PowerPoint and Excel to support solution recommendations and stakeholder buy-in.

• Have working familiarity with visualization tools like Power BI / Looker to support business and MI reporting needs.

• Partner with Insurance business stakeholders to translate domain requirements — including IFRS17 reporting, actuarial data needs, policy administration & general corporate functions — into AI-ready data products.

• Collaborate with Finance, Accounting, FP&A, HR, Risk and Management Information (MI) reporting teams to design data solutions that support regulatory reporting, financial close, Workforce planning, and performance management.

• Provide architectural leadership and technical governance across multiple concurrent engagements, ensuring solutions aligning with enterprise standards and industry best practices.

• Act as a trusted advisor and senior point of contact for cross-functional business partners, IT leadership, and external clients, balancing technical depth with business context.

• Drive MLOps best practices, including model deployment, monitoring, retraining pipelines, and lifecycle management in collaboration with data science and engineering teams.

• Mentor and guide data engineers, data scientists, and junior architects, fostering technical excellence and best practices across the team.

• Minimum 15 years of overall IT experience, with a demonstrable track record of progressively senior architecture and delivery roles.

• Minimum 10 years of focused experience in areas like Solution Architecture, data science, data warehousing, data modeling, MLOps, and Artificial Intelligence.

• At least 5 years of consulting experience, including client-facing delivery, solution architecture, and stakeholder management within professional services or consulting engagements.

• Good experience within the BFSI domain, with specific and demonstrable exposure to Insurance industry processes such as IFRS17 and Actuarial functions.

• Good understanding of Enterprise/Corporate Functions, including Finance/Accounting, FP&A (Financial Planning & Analysis), Human Resource and Management Information (MI) reporting.

Technical Skills

• Expert-level proficiency in Databricks — including cluster management, Delta Lake, workflows, and platform administration.

• Proficiency in Unity Catalog for data governance, access control, and lineage management.

• Expert-level proficiency in UML for data and solution modeling, including class, sequence, and entity-relationship diagrams.

• Proficiency in SQL and NoSQL database technologies and query optimization.

• Strong experience designing, building, and optimizing data pipelines (batch and streaming) using modern data engineering tools and frameworks.

• Sound knowledge of ETL/ELT tools such as DBT, PySpark, Azure Data Factory (ADF), Informatica, Cloud Composer, and Apache Airflow.

• Solid understanding of data warehousing concepts, dimensional modeling, and modern Lakehouse architectures.

• Working knowledge of MLOps tooling and practices for model deployment, monitoring, versioning, and governance.

• Sound knowledge of Agentic AI and the full AI Stack, including platforms such as Azure AI Foundry, for building autonomous and assistive AI solutions.

• Knowledge of AI-SDLC practices, including Red Teaming and Evaluation methodologies, to ensure responsible and robust AI deployment.

• Very good hands-on experience delivering cloud-based projects, ideally across both Azure and GCP.

• Good PowerPoint and Excel skills for executive communication, business case development, and data analysis.

• Skill in visualization tools such as Power BI or Looker will be an added advantage.

• Some relevant industry certifications that will be added advantage, such as (but not limited to):

• Databricks Certified Data Engineer Professional / Solutions Architect

• Microsoft Azure / AWS / Google Cloud certifications

• Other traditional RDBMS (like Oracle) certifications

• TOGAF or other enterprise architecture certifications are a plus

• Any professional training or certification on Microsoft Azure (e.g., Azure Solutions Architect, Azure Data Engineer, Azure AI Engineer) will be an added advantage.

• Bachelor's or Master's degree in Information Technology, Engineering, Science, or a related field.

• Strategic and analytical thinking with the ability to translate ambiguous business problems into structured technical solutions.

• Excellent communication, stakeholder management, and consulting skills.

• Strong leadership and mentoring capability within technical teams.

• Commitment to quality, governance, and best-practice architecture standards.

Prudential is an equal opportunity employer. We provide equality of opportunity of benefits for all who apply and who perform work for our organisation irrespective of sex, race, age, ethnic origin, educational, social and cultural background, marital status, pregnancy and maternity, religion or belief, disability or part-time / fixed-term work, or any other status protected by applicable law. We encourage the same standards from our recruitment and third-party suppliers taking into account the context of grade, job and location. We also allow for reasonable adjustments to support people with individual physical or mental health requirements.