4 days ago
Singapore, SingaporeStaff+
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 to reduce one-off integrations and accelerate delivery.
- Design and lead scalable data ingestion, transformation, orchestration, and serving patterns for structured, semi-structured, and streaming data.
- Own technical architecture for batch, streaming, and event-driven data processing across cloud-native and on-premise environments.
- Drive DataOps practices including automated testing, deployment, monitoring, lineage, data quality checks, and operational observability.
- 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.
- Lead architecture and code reviews and guide teams on performance, resilience, security, and cost optimization.
- Partner with product, network, AI, and enterprise architecture stakeholders to develop 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 promote a culture of ownership, reuse, and continuous improvement.
Requirements
- Bachelor's degree in Computer Science, Data Engineering, Software Engineering, or a related technical discipline, or equivalent practical experience.
- At least 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 or data warehouse technologies.
- Hands-on experience with container platforms, CI/CD, and infrastructure-as-code, such as Kubernetes, Docker, and Terraform.
- Strong understanding of data modeling, data quality, metadata, lineage, security, and governance principles.
- Ability to communicate architecture decisions clearly and influence engineering teams and senior stakeholders across organizational boundaries.
Benefits
- Singtel offers continuous learning, career growth opportunities, meaningful work, and support at enterprise scale.
Tech Stack
Categories
Data Engineering
About Singtel
Singtel is a Singapore‑headquartered public telecommunications group founded in 1879 that sells mobile, broadband, and enterprise network services to consumers and businesses across Asia-Pacific. It owns Optus in Australia and operates NCS (regional IT services) and Nxera (data centers), and is expanding into AI infrastructure via its RE:AI GPU‑as‑a‑Service. Its revenue comes from connectivity subscriptions and managed services across networks, cloud, cybersecurity, and digital platforms, with equity stakes in regional operators broadening its reach.