全职 Analytics Solution Architect 工作, 薪水 up to SGD 10,000, LTM 公司招聘中 - Ricebowl

We are seeking an experienced Analytics Architect with strong expertise in Azure Databricks and Microsoft Fabric to lead the architecture, design, and delivery of advanced analytics and big data solutions. This role requires deep hands‑on experience in data engineering, cloud‑native analytics platforms, and large‑scale data processing, along with the ability to guide teams and engage closely with business stakeholders.

The ideal candidate will bring strong technical leadership, a solid understanding of end‑to‑end data architectures, and a passion for driving scalable, secure, and high‑performance analytics solutions on Azure.

Key Responsibilities

• Lead the architecture, design, and implementation of advanced analytics solutions using Azure Databricks and Microsoft Fabric
• Design and deliver solutions on Microsoft Fabric, including Fabric Pipelines, Lakehouse, Warehouse, and Real‑Time Analytics (Eventhouse)
• Migrate existing analytics workloads (e.g., Azure Synapse, Databricks, Data Marts) to Microsoft Fabric
• Work closely with business stakeholders and IT teams to understand requirements and translate them into effective technical solutions
• Own the end‑to‑end delivery of data solutions, ensuring alignment with business needs and industry best practices
• Lead development of data pipelines and ETL/ELT processes using Azure Databricks, PySpark, and related tools
• Integrate Azure Databricks with other Azure services such as Azure Data Lake, Azure Synapse, Azure Data Factory, and on‑premise systems
• Provide technical leadership and mentorship to data engineering teams, promoting continuous learning and improvement
• Ensure proper documentation of data architecture, pipelines, processes, and data flows
• Enforce best practices around code quality, data security, scalability, and governance
• Stay current with the latest capabilities and advancements in Databricks, Microsoft Fabric, and Azure analytics services to drive innovation

Essential Technical Skills

• Strong hands‑on experience with Azure Databricks, including cluster management, notebook development, and Delta Lake
• Proficiency in big data technologies such as Spark, Hadoop, and processing frameworks like PySpark
• Deep understanding of Azure Data Lake, Azure Synapse Analytics, and Azure Data Factory
• Experience with ETL/ELT pipelines, data warehousing concepts, and data lake architectures
• Advanced SQL skills and familiarity with NoSQL databases
• Experience with CI/CD pipelines and version control systems such as Git
• Solid knowledge of cloud security best practices

Experience Requirements

• 8+ years of experience developing data ingestion and transformation pipelines using Databricks / Synapse notebooks and Azure Data Factory
• Strong hands‑on experience with Delta Tables, Delta Lake, and Azure Data Lake Storage Gen2
• Proven experience using Auto Loader and Delta Live Tables for efficient data ingestion and transformation
• Expertise in building and optimizing query layers using Databricks SQL
• Demonstrated experience integrating Databricks with Azure Synapse, ADLS Gen2, and Power BI for end‑to‑end analytics solutions
• Prior experience developing, optimizing, and deploying Power BI reports and dashboards
• Hands‑on exposure to modern CI/CD practices in Databricks and cloud‑native environments

Nice to Have Skills

• Power BI for reporting and visualization
• Microsoft Fabric for analytics and integration use cases
• Spark Streaming for real‑time data processing
• Familiarity with Azure Resource Manager (ARM) templates and Infrastructure‑as‑Code (IaC) practices

Soft Skills

• Excellent communication skills with the ability to explain complex technical topics to non‑technical stakeholders
• Strong analytical and problem‑solving mindset
• Proven leadership and mentoring capabilities for managing and guiding data engineering teams
• Proactive, detail‑oriented, and collaborative approach to delivery

Education

• Bachelor's degree in Computer Science, Engineering, or a related field