Data Solution Architect

Systems Limited; Kuala Lumpur; On-site; MYR 180,000 - 300,000; Full time

Job summary

Systems Limited is seeking an experienced Data Solution Architect to design and deliver scalable, secure, and cloud-native data platforms on Azure (preferred) with exposure to AWS. You will engage directly with clients to understand business needs, define solution architecture, and lead successful implementations, governance, and data modeling.

The role requires 12+ years in data engineering and analytics, strong Azure expertise (Data Factory, Synapse, Databricks, Data Lake Storage), and

Qualifications

• 12+ years of experience in Data Engineering and Analytics.
• Strong expertise in Microsoft Azure and knowledge of AWS data services.
• Proven client-facing experience and excellent communication.
• Experience designing modern cloud data platforms and migrations.
• Azure certifications preferred (e.g., Azure Solutions Architect Expert).

Responsibilities

• Design end-to-end data architectures and scalable data platforms on Azure or AWS.
• Lead architecture discussions, workshops, and client engagements.
• Define data models, governance, security, and integration patterns.
• Provide technical leadership to delivery teams during projects.
• Prepare architecture documents and proposals with effort estimates.
• Collaborate with stakeholders across business, engineering, and projects.
• Ensure cost-effective, secure, and compliant cloud data solutions.

Skills

Azure data architectures

Client-facing consulting

Data governance & security

Data architecture design

Python

SQL

Spark

ETL/ELT

Data modeling

Cloud migrations

Tools

Azure Data Factory

Azure Synapse Analytics

Azure Databricks

Azure Data Lake Storage

Microsoft Fabric

AWS data services

Redshift

Glue

EMR

S3

Athena

Lambda

Job description

We are looking for an experienced Data Solution Architect to design and deliver scalable, secure, and cloud-native data platforms. The ideal candidate will have strong expertise in Microsoft Azure (preferred) with exposure to AWS, and the ability to engage directly with clients to understand business needs, define solution architecture, and lead successful implementations.

Responsibilities:

• Design end-to-end data architecture and modern data platforms on Azure (preferred) or AWS.
• Should have good knowledge how to use Agentic AI and LLM’s to build future ready data platforms.
• Engage with clients to gather requirements, conduct workshops, and translate business needs into technical solutions.
• Define data architecture, integration patterns, data models, governance, and security best practices.
• Lead solution design for data warehousing, data lakes, real-time data processing, and analytics.
• Provide technical leadership to delivery teams throughout project execution.
• Prepare architecture documents, solution proposals, and effort estimations.
• Collaborate with business, engineering, and project stakeholders to ensure successful delivery.
• Ensure solutions are scalable, secure, cost-effective, and aligned with industry best practices.

Requirements:

• 12+ years of experience in Data Engineering and Analytics
• Strong expertise in Microsoft Azure (Azure Data Factory, Azure Synapse Analytics, Azure Databricks, Azure Data Lake Storage, Microsoft Fabric is a plus).
• Working knowledge of AWS data services (Redshift, Glue, EMR, S3, Athena, Lambda, etc.).
• Strong experience with SQL, Python, Spark, ETL/ELT, and data modeling.
• Hands-on experience in designing and implementing modern cloud data platforms and cloud migration initiatives.
• Strong understanding of data governance, security, scalability, and performance optimization.
• Proven client-facing experience with excellent communication, stakeholder management, and consulting skills.
• Experience preparing solution architecture, technical proposals, and effort estimations.
• Azure certifications (Azure Solutions Architect Expert and/or Azure Data Engineer Associate) are highly preferred; AWS certifications are an added advantage.
• Experience delivering enterprise data solutions for Banking, Telecom, Retail, Healthcare, or other large-scale organizations is preferred.