Provide domain expertise across 4G EPC, 5G Core, control plane, user plane, roaming, VoLTE, VoNR, IoT, 5G slicing, xDR, session tracing, performance analytics, and end-to-end service correlation.
You will design and implement consent management policies, data sharing safeguards, and compliance validation processes that enable trusted, scalable data flows across partner organisations with varying technical capabilities and institutional priorities.
You will lead high-level data partnerships with key agencies including PA, SportSG, AIC/AAC, NParks, LTA, MOH policy and technical teams, and regional health clusters, securing data sharing agreements and consent frameworks that enable trusted, scalable data flows across the ecosystem. You will translate high-level policy and organisational requirements into clear strategic technical directions for the team, ensuring outputs remain aligned with evolving business and programme needs.
Data Contracts & Governance — Guided Implementation: Implement and maintain agreed data contracts between upstream data producers and downstream ML consumers, following governance standards established with guidance from ML Engineer. Establish access control and retention practices for all AI data assets.
Hands-on AWS data engineering experience with a relevant mix of S3, Glue, Lake Formation, IAM, KMS, Lambda, Step Functions, Event Bridge, CloudWatch, Redshift and MSK/Kinesis.
Actively review and optimise report query performance, improving reliability, speed, and scalability for key business reporting and application use cases.
Develop and govern the semanticmodel in Google Looker as the single source of truth for standardized businessmetrics, dimensions, and reporting definitions.
Hands-On Engineering: Play an active role in day-to-day engineering tasks, coding, reviewing, and designing complex data solutions. Share knowledge and best practices with peers through code review and technical discussion, contributing to a culture of engineering excellence without a formal management remit.