Title:  Specialist Data Hub

About the Role

The Data Engineer, Specialist is a key contributor to DKSH's global data capability, responsible for building and sustaining the cloud data platforms that enable data-driven decisions across markets. In this role, you will shape the integrity and scalability of DKSH's data infrastructure, directly supporting business performance and operational excellence on a global scale.

What You Will Deliver

• Design, develop, and implement end-to-end data pipelines and data integration processes — both batch and real-time — covering data analysis, profiling, cleansing, lineage, mapping, transformation, and the full deployment of Extract, Transform, Load / Extract, Load, Transform (ETL/ELT) solutions.
• Drive continuous improvements in data quality, reliability, and efficiency by monitoring pipeline performance and optimizing ETL/ELT processes to meet evolving business demands.
• Establish and deliver best practices across the data management lifecycle, including modular ETL/ELT development, coding and configuration standards, error handling, auditing, and data archival.
• Identify and implement Artificial Intelligence (AI), automation, and data-driven innovations that streamline operations, reduce manual effort, and measurably improve productivity.
• Ensure all development aligns with data governance policies and Business Intelligence (BI) platform guidelines, maintaining compliance and consistency across environments.
• Partner with Information Technology (IT) team members, Subject Matter Experts (SMEs), vendors, and business stakeholders to translate data needs into effective, goal-aligned solutions.
• Resolve Business-As-Usual (BAU) data issues and change requests efficiently, maintaining thorough documentation of investigations, findings, recommendations, and resolutions.
• Support production monitoring, operational incidents, and service requests, including standby support as required on a rotation basis within the team.

What You Bring

• Bachelor's degree in Computing, Information Technology, or equivalent.
• Fresh graduate or 1-3 year of relevant working experience.
• Hands-on experience with Microsoft Fabric, including Lakehouse, Warehouse, Data Pipeline, OneLake, Notebook, and deployment pipelines.
• Practical experience with Azure Data Services, including Azure Synapse Spark, Synapse Database, Azure Data Factory, Databricks, and Azure Data Lake Storage.
• Solid grounding in ETL/ELT frameworks, data warehousing concepts, data management frameworks, and data lifecycle processes.
• Proven ability to handle and process structured, semi-structured, and unstructured data effectively.
• Proficiency in Python, PySpark, and Structured Query Language (SQL) for data engineering development.
• Experience using Azure DevOps to implement Continuous Integration and Continuous Deployment (CI/CD) workflows and manage ETL job deployments across multiple environments.
• Strong knowledge of database technologies, including Relational Database Management Systems (RDBMS), NoSQL, and columnar databases.
• Strong awareness of AI technologies with the ability to apply AI solutions, automation, and analytics to simplify processes and drive operational efficiency.
• Clear and effective communicator, able to present technical concepts to both technical and non-technical audiences.
• Self-driven and collaborative, with the ability to work independently and contribute effectively within diverse, multi-stakeholder teams.
• High sense of ownership, strong affinity for data, and a continuous improvement mindset.
• Knowledge of SAP is an added advantage.

Why Join DKSH