Job Description

Singapore, Singapore
Company: Singtel Group
An empowering career at Singtel begins with a Hello. Our purpose, to Empower Every Generation, connects people to the possibilities they need to excel. Every "hello" at Singtel opens doors to new initiatives, growth, and BIG possibilities that takes your career to new heights. So, when you say hello to us, you are really empowered to say..."Hello BIG Possibilities".
Powering the Future with AIDA
To lead the next phase of our AI evolution, we've launched a new business unit AIDA - Artificial Intelligence & Data Analytics - a strategic engine driving our transformation designed to scale our AI ambitions with precision and purpose. This marks a pivotal shift in how we operate, innovate, and serve to embed intelligence into every layer of our business.
At Singtel, this is more than a technology upgrade. It's a strategic transformation that redefines how value is created across the enterprise core- augmenting human capabilities and unlocking entirely new potential. It is a transformation journey by aligning people, platforms, and processes under one cohesive strategy. Our mission is to build AI literacy, and foster a culture where intelligence empowers people.
We welcome you to join us on a transformational journey that's reshaping the telecommunications industry - and redefining what's possible with AI at its core. Grow with us in a workplace that champions innovation, embraces agility, and puts human potential at the heart of everything we do.
Be a Part of Something BIG!
The Senior Data & Integration Architect plays a critical role in designing and implementing the data and integration layer of Singtel's next-generation AI platform. This role focuses on orchestrating secure, scalable, and interoperable data architectures and API integration frameworks that support advanced AI and ML workloads across the enterprise.
You will work closely with the AI architecture, security, platform, and business teams to ensure seamless data movement, governance alignment, and real-time system interoperability for serving as the bridge between distributed data systems, cloud services, and AI-enabled applications.
Make An Impact By

• Design, build and implement enterprise-wide data and API integration frameworks to support AI/ML platforms across hybrid cloud and on-premise environments
• Work with system owners and data domain leads to design and deliver scalable end-to-end data flows across operational, analytical, and AI systems
• Define and develop secure, reusable API interfaces (REST, GraphQL, event-driven) and data interface (batch or streaming) that enable seamless interoperability between internal systems and AI services
• Oversee and evaluate new data integration approaches and pipeline designs to ensure efficient, secure, and scalable data flow between data sources and AI platforms.
• Collaborate with Security and Data Governance teams to ensure integration designs align with compliance, privacy, and policy requirements (e.g., PDPA, data classification)
• Design and enable data access strategies for LLMs and agent-based workflows, ensuring context-rich, real-time connectivity to distributed enterprise systems
• Implement and maintain integration middleware and tooling (e.g. Kafka, Azure ML/Foundry, Databricks, etc) to support data orchestration, synchronization, and reliability
• Contribute integration expertise to data or AI experimentation, PoCs, and platform upgrades, ensuring architectural consistency and production-readiness
• Define and enforce data and integration design standards, focusing on scalability, resilience, observability, and system decoupling
• Work closely with business units, IT, and Networks to align integration plans with enterprise priorities and ensure successful data exchange across functional boundaries

Skills to Succee

• Bachelor's in Computer Science, Engineering, Data, AI/ML, or related field.
• At least 3 years of experience in data architecture, system and API integration engineering.
• Demonstrated experience in designing integration flows for large-scale, real-time systems across cloud and legacy environments.
• Experience in designing and implementing data integration frameworks across hybrid cloud and on-premise environments, including building scalable and secure data pipelines for AI/ML platforms.
• Proficient in data integration design, with solid knowledge of data pipelines, data lakes, data warehouses, and data lakehouse architectures.
• Good knowledge of modern data orchestration and middleware tools such as Apache Kafka, Azure Data Factory, Databricks, Airflow, and experience in managing data flow between operational, analytical, and AI environments.
• Working knowledge of data security, data protection and data quality management including implementation of encryption, RBAC, masking, and alignment with regulatory frameworks such as PDPA and internal data classification policies.
• Proven experience integrating data systems with AI/ML workflows, including model training, serving, monitoring, and enabling context-aware access for LLMs and agent-based automation.
• Effective collaboration skills to work across data, platform, machine learning engineering and API integration teams, with a clear communication style to bridge business and technical stakeholders
• Good internal (IT, Networks, business) and external (suppliers, government) stakeholders management skills
• Strong technical writing and presentation skills, with the ability to communicate complex concepts clearly to both technical and non-technical stakeholders.
• Proactive and fast learner with a strong drive to stay current on emerging technologies and industry trends.

Rewards that Go Beyond

• Full suite of health and wellness benefits
• Ongoing training and development programs
• Internal mobility opportunities

Your Career Growth Starts Here. Apply Now!
We are committed to a safe and healthy environment for our employees & customers and will require all prospective employees to be fully vaccinated.

Skills Required