Senior Data Platform Architect for AI & Analytics

Singtel Group; Singapore; On-site; SGD 140,000 - 230,000; Full time

Job summary

Singtel Group is building an AI-first telco and seeks an experienced Data Platform Architect to lead the architecture for enterprise-scale data platforms, enabling AI, analytics and autonomous network use cases across cloud-native and on-premise environments.

You will establish reusable data products, drive DataOps maturity and collaborate with product, network and EA stakeholders to translate strategy into a practical data platform roadmap.

Qualifications

• Bachelor's degree in Computer Science, Data Engineering, or a related technical discipline, or equivalent practical experience.
• Min 8 years of relevant experience in data engineering, software engineering or data platform engineering, including substantial experience leading solution design or technical delivery.
• Strong proficiency in Python and SQL; working knowledge of Java and/or Scala is beneficial.
• Strong experience with distributed data processing and streaming technologies such as Apache Spark, Kafka and/or Flink.
• Experience designing cloud-native data platforms using one or more major cloud ecosystems and modern lakehouse/data warehouse technologies.
• Hands-on experience with container platforms, CI/CD and infrastructure-as-code, for example Kubernetes, Docker and Terraform.
• Strong understanding of data modelling, data quality, metadata, lineage, security and governance principles.
• Ability to communicate architecture decisions clearly to engineering teams and senior stakeholders, and to influence across organisational boundaries.

Responsibilities

• Lead the architecture and evolution of enterprise-scale data platforms for AI, advanced analytics and Autonomous Network use cases.
• Establish reusable data products and platform services that reduce one-off integrations and accelerate delivery across teams.
• Raise engineering maturity through DataOps, automated testing, observability, CI/CD, infrastructure-as-code and AI-assisted engineering practices.
• Strengthen trust in enterprise data through data quality, lineage, metadata, security and governance-by-design.
• Own the technical architecture for batch, streaming and event-driven data processing across cloud-native and on-premise environments.
• Design and lead implementation of scalable data ingestion, transformation, orchestration and serving patterns for structured, semi-structured and streaming data.
• Define engineering standards, reference architectures, reusable frameworks and design patterns for data products and platform services.
• Enable AI and GenAI workloads through production-grade datasets, feature pipelines, retrieval data flows, vector stores and related data services where appropriate.
• Drive DataOps practices including automated testing, deployment, monitoring, lineage, data quality checks and operational observability.
• Lead architecture and code reviews, resolve complex engineering trade-offs, and guide teams on performance, resilience, security and cost optimisation.
• Partner with product, network, AI and enterprise architecture stakeholders to translate strategic outcomes into an executable data platform roadmap.
• Evaluate emerging technologies and recommend adoption based on measurable value, interoperability, operational fit and total cost of ownership.
• Coach and mentor engineers, build technical capability and promote a strong engineering culture focused on ownership, reuse and continuous improvement.

Skills

Python

SQL

Leadership

Architecture discussions

Education

Bachelor's degree in Computer Science/Data Engineering

Tools

Kubernetes

Docker

Terraform

Apache Spark

Kafka

Flink

Job description

Singtel Group is building an AI-first telco and seeks an experienced Data Platform Architect to lead the architecture for enterprise-scale data platforms, enabling AI, analytics and autonomous network use cases across cloud-native and on-premise environments.

You will establish reusable data products, drive DataOps maturity and collaborate with product, network and EA stakeholders to translate strategy into a practical data platform roadmap.