Data Solutions Architect

EPAM Systems; Malaysia; Ibrido; MYR 180.000 - 320.000; Tempo pieno

Descrizione del lavoro

EPAM Systems Inc. is seeking a Data Solutions Architect in Kuala Lumpur with hybrid work. You will design scalable data architectures across Azure, AWS, or GCP and partner with stakeholders to shape secure, cost-aware platforms.

Responsibilities include defining data pipelines, data warehouses, governance, and leading architecture workshops. You will guide tool selections such as Snowflake and Databricks, and document trade-offs for delivery teams.

Competenze

• 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.

Mansioni

• 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

Conoscenze

Data architecture

Cloud data platforms

Data pipelines

Data warehousing

SQL

Data governance

Security fundamentals

Python

Scala

Java

Documentation

Stakeholder communication

Strumenti

Azure

AWS

GCP

Snowflake

Databricks

Collibra

Purview

Kafka

Descrizione del lavoro

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