IT ADI Analyst

Job description

Position Snapshot Location: Petaling Jaya, Malaysia Company: Nestlé Malaysia & Singapore Full-time Bachelor's Degree 5+ years of experience Position Summary Joining Nestlé means you are joining the largest Food and Beverage Company in the world. At our very core, we are a human environment – passionate people driven by the purpose of enhancing the quality of life and contributing to a healthier future. We are looking for an IT ADI Analyst with reliability, governance and AI readiness of our MYSG data foundations. The role will design and operate secure, scalable and reusable cloud data solutions, pipelines and data products, while enabling trusted data capabilities for analytics, automation, machine learning and GenAI. You will work closely with business stakeholders, regional and enterprise data teams to translate complex business requirements into scalable technical solutions, while ensuring strong governance, security, quality and operational reliability. A Day in the Life of an IT ADI Analyst Cloud Data Engineering & Data Product Leadership Design, build and optimise scalable cloud-based data ingestion, transformation, harmonisation and serving pipelines across enterprise and local data sources. Design and manage modern cloud data solutions using Snowflake, Microsoft Azure, Azure Data Factory, Azure data services and Databricks. Develop reusable, well-documented and business-ready data products following a reuse-first approach. Define data models, interfaces, metadata, lineage, retention and lifecycle controls. Lead technical design, code reviews, testing and release quality for complex data initiatives. Support strategic MYSG capabilities and analytics, automation and AI use cases. Cloud Platform Reliability & Cost Optimisation Own the technical health, availability and performance of MYSG cloud data services. Apply cloud architecture practices covering scalability, resilience, security, performance and recoverability. Implement monitoring, alerting, data quality rules, anomaly detection and root-cause management. Apply DataOps, DevOps and CI/CD practices to improve deployment and operational efficiency. Optimise Snowflake workloads, cloud capacity, storage and compute consumption. Automate repeatable operations and reduce manual support effort and technical debt. Security, Compliance & Data Governance Ensure data solutions comply with Nestlé's security, privacy, architecture and data governance requirements. Implement role-based access, audit logging, monitoring, segregation of duties and controlled release practices. Partner with Data Owners, Business Stewards and Data Stewards to establish data quality rules, ownership and certification. Maintain audit readiness and drive timely remediation of identified risks and findings. Ensure data access is properly governed while preventing duplication and unmanaged data silos. Stakeholder Management & AI Readiness Act as a key technical liaison between ADI and business stakeholders, building strong and trusted working relationships. Understand business objectives, pain points and data requirements and translate them into scalable technical solutions. Communicate technical concepts, trade-offs, risks, dependencies, costs and delivery implications in clear business language. Prepare trusted, discoverable and machine-consumable datasets for advanced analytics, machine learning, GenAI and agentic solutions. Partner with Commercial, Finance, Supply Chain, Technical & Production, MDO, regional ADI and enterprise data teams. Mentor ADI colleagues, conduct peer reviews and share modern engineering practices. Supplier & Strategic Partner Management Coordinate technology partners and vendors involved in platform, integration, data or security initiatives. Define technical acceptance criteria and ensure delivery quality, documentation, supportability and knowledge transfer. Identify and escalate delivery, performance, compliance and commercial risks through the appropriate governance channels. What Will Make You Successful Bachelor's degree in Computer Science, Information Technology, Data Engineering or a related discipline, or equivalent experience. Strong hands-on experience delivering enterprise-scale cloud data engineering or data platform solutions. Practical experience with modern cloud data management platforms, preferably Snowflake and Microsoft Azure. Strong expertise in Snowflake, including data modelling, workload design, performance optimisation, access management and cost-conscious use of compute and storage. Strong working knowledge of Microsoft Azure data services, including Azure Data Factory and Azure data storage. Experience with Databricks and Microsoft Fabric is an advantage. Strong technical knowledge of SQL, ETL/ELT, APIs, integration patterns and enterprise data modelling. Experience with Enterprise Data Domains, data products, metadata, lineage, cataloguing, data quality and observability. Understanding of AI-ready data architecture, semantic models and ML/GenAI data requirements. Experience with DataOps, DevOps, CI/CD, testing, release management and operational readiness. Working knowledge of security, privacy, RBAC, audit controls and segregation of duties. Strong stakeholder management and business partnering skills, with the ability to translate between business needs and technical solutions. Experience working across a complex, multi-market and virtual environment. Demonstrated experience in mentoring, peer review, technical standards and knowledge sharing. Relevant cloud, Snowflake, Microsoft Azure, data engineering or platform certification is preferred. Knowledge of the MYSG commercial and operational data landscape is an advantage.