Data Engineer - Associate Manager

Information Technology Services (ITS) team is responsible for providing quality IT services and solutions internally to support the business and improve efficiency. You will be part of the Data Office, the department responsible for defining and implementing the Singapore firm's Data and analytics strategy. The team works with a vision to empower people at KPMG to harness data across the firm to generate actionable insights and drive value.

We're looking for a resourceful and trustworthy team player who is passionate about data and technology and enjoys diagnosing and solving problems in complex systems. As a senior member of data team, your responsibilities include (but are not limited to):

Responsibilities:

• Support the implementation and continuous improvement of the enterprise data platform, enabling the business to leverage internal and third party data sets with strong data quality and efficiency.
• Understand KPMG's data landscape, IT and business priorities, and success measures to design and deliver fit for purpose data architecture capabilities.
• Design and implement Lakehouse (Medallion) architecture using Delta Lake and Unity Catalog.
• Define and enforce engineering standards (data modeling, coding conventions, reusable pipeline templates, and design reviews).
• Own CI/CD for data (Azure DevOps/Git), including environment promotion, secrets management, and automated testing.
• Design, develop, and maintain data integration and transformation solutions using Azure Databricks and Synapse Analytics
• Build scalable and reliable data pipelines for ingestion, processing, and analytics using Spark (batch and, where required, streaming).
• Develop and optimize ETL/ELT processes to ingest data from diverse sources into curated, analytics ready data products.
• Deploy and operate data solutions across environments (Dev, QA, STG, Prod) and manage the end to end release lifecycle.
• Apply best practices for data governance, security, and compliance, and drive performance and cost optimisation through job tuning and workload profiling.
• Monitor and troubleshoot data pipelines in production, resolving issues to ensure reliable operations and timely, accurate data delivery.
• Identify and resolve performance bottlenecks and ensure platform SLAs are met through proactive monitoring and optimisation.
• Ensure platform components (infrastructure and services) are updated and operating as expected; coordinate maintenance and disaster recovery activities with infrastructure support teams to minimise disruption.

Required Skills:

• Degree in Computer Science, IT, Information Management, or a similar field.
• Minimum 6 years of experience in a similar role, with a proven track record of building scalable and performant data platforms.
• Hands-on experience designing and managing data warehouse solutions using Azure databricks and Synapse Analytics.
• Proficient in SQL and Python, with proven experience building and orchestrating complex ETL/ELT workflows and automating data movement across environments.
• Strong troubleshooting skills with the ability to diagnose and resolve complex issues in data pipelines and workflows.
• Working knowledge of DataOps practices, including configuration management, automation, CI/CD (e.g., Azure DevOps), and version control (Git).
• Familiarity with metadata management, data quality, and data catalog solutions (e.g., Microsoft Purview, Informatica IDMC).
• Familiarity with Microsoft Fabric, including Lakehouse and OneLake concepts.
• Azure certifications (e.g., Azure Data Engineer Associate) are a plus.