Associate Director, Data & AI Architect
Associate Director, Data & AI Architect
prudential services asiaEarly Applicant
- Posted a month ago
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Job Description
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.
Job Responsibilities
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.
Job Responsibilities
- 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.
- 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.
More Info
Key Skills
Looker
Azure AI Foundry
Unity Catalog
Cloud Composer
Agentic AI


