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Company Overview
This organization is a leading player in digital transformation and data-driven solutions, helping businesses leverage their data assets for strategic insights, operational efficiency, and scalable innovation. They focus on creating robust data architectures, pipelines, and AI-enabled analytics platforms to empower decision-making across global operations.
Job Title: Data Engineer, Digital Transformation & Data (DT&D) Location: Singapore Employment Type: Regular
Job Description Reporting to the Data and Analytics Lead, the successful candidate will be responsible for the following:
Data Management & Transformation
• Design and develop new data pipelines and manage existing pipelines extracting data from business applications, databases, and external systems.
• Implement data quality checks and validations to ensure accuracy, consistency, and completeness of data.
• Transform data using cleansing, aggregation, filtering, and enrichment techniques.
• Establish governance for data and algorithms used in analysis, analytical applications, and automated decision-making.
• Manage logical and physical data models to capture structure, relationships, and constraints of datasets.
• Ensure compliance with security and governance best practices.
Optimization & Automation
• Implement and maintain CI/CD pipelines for deployments and cloud resource provisioning.
• Optimize data pipelines and workflows for performance, scalability, and efficiency.
• Optimize models and algorithms for data quality, security, governance, and performance.
• Assess processing and storage capacity for the data warehouse and ETL platforms, including capacity planning and forecasting.
• Monitor and tune data systems, resolving performance bottlenecks, and applying caching and indexing strategies.
• Monitor platform credit consumption and housekeeping.
• Support deployment and maintenance of AI solutions on the data platform.
Collaboration
• Work with the Data Lead and business users to manage data as a business asset.
• Guide business users in creating and maintaining reports and dashboards.
Job Requirements
• Bachelor’s degree in computer science, data science, software engineering, information systems, or related quantitative field; Master’s degree preferred.
• Minimum ten years of experience in data management disciplines, including integration, modeling, optimization, and data quality.
• At least four years of experience designing and implementing data architectures on Azure cloud services and Databricks.
• Strong proficiency in Python (PySpark) and SQL; experience with Java or Scala is a plus.
• Experience with relational and non-relational databases (SQL, NoSQL); familiarity with Oracle preferred.
• Experience using Azure DevOps, Databricks LakeFlow Jobs for version control, CI/CD, and pipeline deployment.
• Familiarity with data catalog tools such as Unity Catalog and Microsoft Purview.
• Experience with BI and visualization tools (Power BI, Python visual packages) preferred.
• Experience supporting AI/ML model deployment, feature engineering, and production inference preferred.
• Demonstrates core values including Integrity, Teamwork, Accountability, Agility, and Ambition.
Disclaimer
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