Lead Data Engineer

About the role

Singtel is looking for a Lead Data Engineer to lead the architecture and evolution of enterprise-scale data platforms for AI, advanced analytics and Autonomous Network use cases. The role establishes reusable data products and platform services, raises engineering maturity through DataOps and observability, and owns the technical architecture for batch, streaming and event-driven data processing across cloud-native and on-premise environments.

Key responsibilities

• 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.
• 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 turn strategy into an executable data platform roadmap.
• Evaluate emerging technologies and recommend adoption based on value, interoperability, operational fit and total cost of ownership.
• Coach and mentor engineers and build technical capability.

Required profile

• Bachelor's degree in Computer Science, Data Engineering, Software Engineering or a related technical discipline, or equivalent practical experience.
• Minimum 8 years of relevant experience in data engineering, software engineering or data platform engineering, including substantial experience leading solution design or technical delivery.
• 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.

Required skills

• Strong proficiency in Python and SQL; working knowledge of Java and/or Scala is beneficial.
• Distributed data processing and streaming technologies such as Apache Spark, Kafka and/or Flink.
• Cloud-native data platforms using major cloud ecosystems and modern lakehouse/data warehouse technologies.
• Container platforms, CI/CD and infrastructure-as-code, for example Kubernetes, Docker and Terraform.