Data & AI Engineer (Deputy Manager)

Takaful Malaysia; Kuala Lumpur; On-site; MYR 180,000 - 300,000; Full time

Job summary

Takaful Malaysia is seeking an experienced professional to design, develop, and deliver data, analytics, and AI solutions that enable data‑driven decisions and enterprise transformation. You will lead hands-on development and provide functional leadership across stakeholders and governance teams.

You will work on building, standardizing, and maturing the Enterprise Data Platform, ensuring security, compliance, and long-term value realization across transformation phases.

Qualifications

• Minimum 5–6 years in data/analytics/AI delivery roles with transformation experience.
• Experience in enterprise data platforms and architecture, with governance alignment.
• Regulated financial services environment experience is preferred.
• Certifications in cloud data and AI are strongly required or preferred.

Responsibilities

• Design, build, and evolve the Enterprise Data Platform (EDP) to enable transformation initiatives.
• Lead foundational EDP capabilities: ingestion, storage, processing, analytics, AI enablement.
• Standardize and industrialize data/analytics platforms across transformation phases.
• Translate priorities into EDP requirements, roadmaps, and architecture components.
• Develop data pipelines, datasets, dashboards, and AI/ML models integrated with the EDP.
• Collaborate with stakeholders to identify and deliver high-impact use cases.
• Ensure security, privacy, resilience, and regulatory compliance with governance.
• Provide technical mentorship to juniors and contributors on EDP delivery.

Skills

Data pipelines

Dashboards

AI/ML models

Data governance

Security & privacy

Stakeholder collaboration

Mentorship

Enterprise data platforms

Architecture guidance

Regulatory compliance

Education

Master's degree in Data Science, AI, Analytics

Bachelor's degree in Data Science, Computer Science, IT, Engineering, Math, Statistics

Diploma in a relevant discipline with extensive data/analytics/AI experience

Professional certifications in Big Data, Analytics, or AI

Tools

Databricks

Hadoop ecosystem

Spark

Job description

The purpose of this position is to design, develop, and deliver data, analytics, and AI solutions that enable data-driven decision-making and support enterprise-wide transformation initiatives. The position plays a key role in shaping the organization’s data and AI journey. The role combines hands-on technical delivery with functional leadership, ensuring that data and AI use cases are practical, scalable, secure, and aligned with business priorities and enterprise standards.

Operating at a deputy manager / senior developer level, the role works closely with business stakeholders, transformation teams, IT, data platform teams, cybersecurity functions, and governance to translate business needs into high-quality and secure data and AI solutions. Where enterprise data platforms, tools, or capabilities exist, the role is responsible for enhancing, standardizing, and maturing them. Where such capabilities do not yet exist, the role leads the design and development of foundational data and AI solutions in collaboration with business, IT, and governance stakeholders, ensuring sustainability, governance alignment, and long-term value realisation.

Job Requirement

• Drive and support the design, build, and evolution of the Enterprise Data Platform (EDP) as a core enabler of the group’s transformation initiatives
• Lead the establishment of foundational EDP capabilities where none exist, including data ingestion, storage, processing, analytics, and AI enablement layers
• Enhance, standardize, and industrialize existing data and analytics platforms as the organization progresses through different transformation phases
• Translate business and transformation priorities into clear EDP requirements, architecture components, and delivery roadmaps, aligned with enterprise architecture guidance
• Perform hands-on development of data pipelines, analytical datasets, dashboards, and AI/ML models that are built on or integrated with the EDP
• Work closely with business stakeholders, analysts, and transformation leads to identify, priorities, and deliver high-impact data and AI use cases enabled by the EDP
• Collaborate with IT, infrastructure, cybersecurity, data governance, and CISO teams to ensure the EDP and related solutions meet enterprise standards for security, privacy, resilience, and regulatory compliance
• Define and implement data governance, data quality, metadata, and access control practices as part of the EDP operating model
• Support decisions on technology selection, platform design, and tooling for the EDP, balancing speed of delivery with long-term scalability and sustainability
• Oversee deployment, monitoring, and continuous improvement of EDP components and data products to ensure reliability and value realization
• Provide technical guidance and mentorship to junior resources or contributors involved in EDP and data solution delivery
• Stay current on data platforms, analytics, and AI trends, recommending pragmatic enhancements aligned with enterprise readiness and transformation objectives

Qualification

• Master's degree in Data Science, Artificial Intelligence, Analytics, or a related field, with a minimum of 5–6 years of relevant experience in data, analytics, or AI delivery roles, including involvement in enterprise or transformation initiatives; OR
• Bachelor's degree in Data Science, Computer Science, Information Technology, Engineering, Mathematics, Statistics, or a related discipline, with a minimum of 6–8 years of hands-on experience in data engineering, analytics, or AI solution development within the financial services industry or regulated enterprise environments; OR
• Diploma in a relevant discipline, with a minimum of 8–10 years of progressive experience in data, analytics, or AI development within regulated enterprise environments.
• Professional certifications in Big Data, Analytics, or AI are strongly required or highly preferred, such as:
• Cloud data and AI certifications (e.g. Azure Data Engineer / AI Engineer, AWS Data Analytics / Machine Learning, GCP Data Engineer)
• Big data platform certifications (e.g. Databricks, Hadoop ecosystem, Spark)
• AI / machine learning certifications from recognized industry or academic providers