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Design end-to-end cloud data architectures on Azure, AWS or GCP
Define data pipeline, data warehouse and integration patterns
Lead architecture workshops and document decisions, trade-offs and standards
Guide platform selection across Snowflake, Databricks and related services
Embed governance, security and cost optimization into designs
Design end-to-end cloud data architectures across Microsoft Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP)
Define data pipeline, data warehouse and integration patterns aligned to target architecture
Lead architecture workshops and document decisions, trade-offs and standards
Guide platform selection and implementation approaches across Snowflake, Databricks and related services
Embed governance, security and cost optimization practices into designs
Proven experience designing data solutions in client-facing environments
Hands-on experience with cloud data platforms on Azure, AWS, or GCP
Strong SQL capability with the ability to guide performance and data access approaches
Strong knowledge of data pipelines, data warehousing concepts and integration patterns
Proficiency in Python, Scala, or Java
Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
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Day 0
Early. Similar jobs usually come down between day 7 and day 53.
From 7,794 similar postings that came down. Coming down is not always a hire.
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We are seeking a Data Solutions Architect in Kuala Lumpur (hybrid). You will design cloud data architectures and scalable pipelines across Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP). Partner with client stakeholders to shape secure, governed, cost-aware platforms and guide delivery teams with clear design decisions and documentation. Responsibilities Partner with business and technical stakeholders to define requirements and translate them into solution designs Design end-to-end cloud data architectures across Microsoft Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP) Define data pipeline, data warehouse and integration patterns aligned to target architecture Lead architecture workshops and document decisions, trade-offs and standards Guide platform selection and implementation approaches across Snowflake, Databricks and related services Support solution shaping, estimation and delivery approach inputs for new engagements Embed governance, security and cost optimization practices into designs Assess where Generative AI and large language model (LLM) patterns can improve data solutions Requirements Proven experience designing data solutions in client-facing environments Hands-on experience with cloud data platforms on Azure, AWS, or GCP Strong knowledge of data pipelines, data warehousing concepts and integration patterns Strong SQL capability with the ability to guide performance and data access approaches Working knowledge of data governance and security fundamentals Proficiency in Python, Scala, or Java Clear communication in English with confidence engaging client stakeholders Ability to create practical architecture documentation and communicate trade-offs Nice to have Exposure to artificial intelligence and machine learning (AI/ML) or machine learning operations (MLOps) pipelines Familiarity with metadata management tools such as Collibra or Microsoft Purview Experience with real-time or high-volume processing including Kafka and streaming
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Malaysia
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