Data Architect - Fabric

Systems Limited - APAC; Kuala Lumpur; On-site; MYR 180,000 - 360,000; Full time

Job summary

Systems Limited - APAC seeks an experienced Data Architect to design and lead enterprise cloud data platforms using Microsoft Fabric and Azure Data Services. The role focuses on end-to-end architecture, scalable data models, and real-time analytics across the organisation.

You will shape data governance, security, and performance while mentoring engineers and collaborating with stakeholders to deliver scalable solutions.

Qualifications

• Bachelor's or Master's degree in Computer Science, Software Engineering, IT, Data Engineering, or a related discipline.
• 10+ years of experience in Data Architecture, Cloud Data Platforms, Data Engineering, and Enterprise Analytics.
• Hands-on experience with Microsoft Fabric components and Azure services.
• Proven enterprise data modeling experience across conceptual, logical, and physical tiers.
• Strong background in ETL/ELT, data ingestion, streaming, and data governance.
• Experience building real-time data platforms and implementing CI/CD for data solutions.

Responsibilities

• Lead end-to-end architecture and implementation of enterprise cloud data platforms using Microsoft Fabric.
• Design scalable, secure, high-performance data architectures aligned with business strategies.
• Develop conceptual, logical, and physical data models to support analytics.
• Architect modern data engineering solutions with Fabric components like OneLake and Data Factory.
• Design and govern data ingestion, transformation, orchestration, and ELT/ETL pipelines.
• Implement real-time streaming architectures using Spark Structured Streaming and related tools.
• Define architecture standards, reusable frameworks, and best practices across teams.
• Collaborate with stakeholders to translate requirements into scalable technical solutions.
• Ensure performance, governance, security, and cost optimization across cloud environments.
• Provide technical leadership, mentorship, and architecture reviews.

Skills

Microsoft Fabric

Azure Data Services

Data Modeling

Python / PySpark

SQL

ETL / ELT Pipelines

Real-Time Streaming

Cloud Architecture

Data Governance

CI/CD / DevOps for data

Education

Bachelor's or Master's in Computer Science / Software Engineering / IT / Data Engineering

Tools

OneLake

Data Factory

Lakehouse

Data Warehouse

Spark Notebooks

Real-Time Intelligence

Azure Synapse Analytics

Azure Event Hubs

Job description

The Data Architect is responsible for designing and leading enterprise-scale cloud data platforms using Microsoft Fabric and Azure Data Services. The role focuses on defining end-to-end architecture, developing scalable data models, building modern data engineering and real-time streaming solutions, and enabling advanced analytics across the organization.

Responsibilities

• Lead the end-to-end architecture, design, and implementation of enterprise data platforms using Microsoft Fabric.
• Design scalable, secure, and high-performance cloud data architectures aligned with business and technology strategies.
• Develop and maintain conceptual, logical, and physical data models to support enterprise reporting and analytics.
• Architect modern data engineering solutions utilizing Microsoft Fabric components including OneLake, Data Factory, Data Warehouse, Lakehouse, Spark, and Real-Time Intelligence.
• Design, optimize, and govern data ingestion, transformation, integration, orchestration, and ELT/ETL pipelines.
• Design and implement real-time and streaming data architectures using Eventstreams, KQL Databases, Spark Structured Streaming, and other Microsoft Fabric streaming capabilities.
• Define enterprise architecture standards, reusable frameworks, reference architectures, and implementation best practices.
• Collaborate with business stakeholders, solution architects, product owners, and engineering teams to translate business requirements into scalable technical solutions.
• Ensure data platform performance, scalability, reliability, security, governance, and cost optimization across cloud environments.
• Conduct architecture reviews, provide technical leadership, and mentor data engineers and technical teams.
• Establish data governance, metadata management, data quality, and security best practices aligned with organizational policies.
• Evaluate emerging Microsoft Fabric and Azure technologies and recommend continuous improvements to the enterprise data platform.

Requirements

• Bachelor's or Master's degree in Computer Science, Software Engineering, Information Technology, Data Engineering, or a related discipline.
• 10+ years of experience in Data Architecture, Cloud Data Platforms, Data Engineering, and Enterprise Analytics solutions.
• Extensive hands-on experience with Microsoft Fabric, including OneLake, Data Factory, Lakehouse, Data Warehouse, Spark Notebooks, Real-Time Intelligence, Eventstreams, and KQL Databases.
• Proven experience in enterprise data modeling, including conceptual, logical, and physical data models.
• Strong experience designing ETL/ELT pipelines, data integration, orchestration, and workflow automation.
• Experience building real-time and streaming data platforms using Spark Structured Streaming, Eventstreams, Kafka, or similar technologies.
• Advanced SQL and strong programming experience in Python and/or PySpark.
• Experience with Azure services such as Azure Data Factory, Azure Synapse Analytics, Azure Data Lake Storage, Azure Event Hubs, Azure Functions, Azure DevOps, and Microsoft Entra ID.
• Strong understanding of cloud architecture principles, distributed computing, data security, governance, and performance optimization.
• Experience implementing CI/CD pipelines, Infrastructure as Code, and DevOps practices for data platforms.
• Knowledge of enterprise data governance, data quality, metadata management, and regulatory compliance.
• Strong stakeholder management, communication, leadership, and mentoring skills.
• Microsoft Fabric, Azure Data Engineer, Azure Solutions Architect, or related Microsoft certifications are highly preferred.