The position is responsible for designing, building, and operating data pipelines and data products purpose-built for AI and advanced analytics use cases. The role focuses on enabling feature engineering, curated datasets, real-time and batch data pipelines, and data quality controls that support machine learning models, generative AI systems, and AI-enabled business services. The successful candidate will work closely with AI platform engineering, data platform teams, MLOps, AI application engineers, security and risk teams, and business stakeholders to ensure AI solutions are powered by accurate, compliant, and production-ready data.

Responsibilities

AI Data Architecture & Pipelines

Design and implement scalable data pipelines to support model training, feature generation, and real-time inference and decisioning
Build and maintain batch and streaming pipelines, including data ingestion from internal and external sources
Ensure data architectures align with AI reference architectures and organisational data and platform standards

Feature Stores & AI Data Products

Design, build, and operate feature stores to support reuse of engineered features and consistency between training and inference
Create curated, AI-ready datasets for data scientists, AI engineers, and product and analytics teams
Enable discoverability and reuse of AI data assets across teams

Data Quality, Lineage & Observability

Implement automated checks for data accuracy, completeness, timeliness, and consistency
Ensure end-to-end data lineage and traceability across AI data pipelines
Build observability capabilities to detect data drift and anomalies, and support root-cause analysis
Collaborate with site reliability engineering (SRE) and platform teams to maintain operational stability

Privacy, Security & Regulatory Compliance

Enforce data privacy, sovereignty, and protection requirements across all AI data assets
Implement data access controls and data masking where required
Ensure AI datasets comply with applicable market regulations and internal security and governance standards
Support audit and regulatory reviews relating to AI data usage

Enablement of AI & Analytics Use Cases

Partner with AI application and MLOps teams to enable rapid experimentation and productionisation
Reduce data preparation effort required for AI use cases
Support both generative AI and classical machine learning/advanced analytics workloads
Balance flexibility for innovation with disciplined data governance

Continuous Improvement & Standardisation

Standardise AI data engineering patterns, tooling, and best practices
Contribute to broader data and AI platform roadmaps
Drive continuous improvement in pipeline reliability, data freshness, and reusability of data products

Experience and education

Education

Master's degree in Computer Science, Big Data, Information Systems, Engineering, Data Science, Artificial Intelligence, or a related field

Experience

5+ years of experience in data engineering or platform data roles
Proven hands-on experience building large-scale data pipelines (batch and streaming)
Experience building feature engineering pipelines
Experience working with cloud data platforms (Microsoft Azure experience required)
Experience working with both structured and unstructured data
Experience in financial services, fintech, telecommunications, or other regulated industries is advantageous
Exposure to AI/ML or advanced analytics workloads is preferred

Technical Competencies

Strong understanding of data pipeline and orchestration patterns
Knowledge of feature store concepts and implementation
Proficiency in streaming and batch data processing
Strong grounding in data quality, lineage, and observability practices
Experience with cloud-native data platforms
Understanding of security and privacy-by-design principles

Behavioural Qualities

Detail-oriented and accuracy-driven
Delivery-focused and accountable
Structured and methodical in approach
Curious and continuously learning
Collaborative and respectful
Comfortable operating at scale and across multiple markets