Technical Architect

Snowflake

. Design and deliver customer solutions on Snowflake across data warehousing, open lakehouse with Apache Iceberg tables, data engineering, and secure data sharing .

Posted 11/11/2026full-timeSingapore • SingaporeMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and delivering customer solutions on Snowflake, including data warehousing and lakehouse architectures. Proficient in building data pipelines and implementing security best practices while leveraging cloud platforms and orchestration tools.

Highest-signal resume keywords

Snowflake Solutions ArchitectureSQL and Python ProficiencyData Warehouse and Lakehouse DesignETL/ELT and Orchestration ToolsSnowflake SnowPro Certification

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLPythonData EngineeringData TransformationData WarehousingOpen Lakehouse ArchitectureMLOpsData Quality FrameworksRole-Based Access ControlAutomated Deployment

Soft Skills

Customer-Facing CommunicationKnowledge TransferCollaboration

Tools & Technologies

SnowflakeApache IcebergOpenflowDbtSnowpipeGitHub ActionsAWSAzureGCPInformatica

Certifications & Qualifications

Snowflake SnowPro Core CertificationSnowflake SnowPro Advanced Certification

Industry Keywords

Data SharingSecure ViewsClean RoomsEnterprise AILarge Data Platform Migrations

Tech Stack

Tools & technologies

AirflowApacheAWSAzureCloudETLGoogle Cloud PlatformInformaticaMatillionPythonSnowflakeSparkSQL

About the role

Key responsibilities & impact

Design and deliver customer solutions on Snowflake across data warehousing, open lakehouse with Apache Iceberg tables, data engineering, and secure data sharing
Build batch and streaming ingestion and data transformation pipelines using Openflow, dbt projects on Snowflake, Snowpipe, Streams and Tasks, Dynamic Tables, and Snowpark
Implement Snowflake security and governance best practices, including role-based access control, masking and row access policies, data quality frameworks, and Snowflake Horizon Catalog
Design and implement open lakehouse architectures leveraging Snowflake-managed Iceberg tables and interoperability with open table formats
Architect and enable secure, zero-copy data collaboration across business units and external partners using Snowflake Data Sharing, Secure Views, and Clean Rooms
Design, build, and deploy scalable data applications across the Snowflake AI Data Cloud using the Native App Framework, SPCS, App Runtime, and Streamlit in Snowflake
Help customers adopt Snowflake Cortex AI features, including Cortex AISQL functions, Cortex Search, Cortex Analyst, and CoCo; deploy MLOps
Set up automated deployment using DCM, Git integration, and GitHub Actions for repeatable, governed releases
Create comprehensive documentation and execute knowledge transfer so customers can maintain, optimize, and extend Snowflake solutions for performance and cost
Partner with System Integrators and share field feedback with Snowflake Product and Engineering teams

Requirements

What you’ll need

5+ years of experience in a customer-facing technical role such as consulting, data engineering, or solutions architecture
8+ years of overall technology experience
Strong hands-on skills in SQL and Python building data-intensive use cases
Experience designing data warehouse, data lake, or lakehouse solutions for enterprise customers
Working knowledge of at least one major cloud platform: AWS, Azure, or GCP
Experience with ETL/ELT and orchestration tools such as dbt, Informatica, Matillion, Fivetran, or Airflow
Ability to travel to customer sites within the region as needed
A degree in computer science, engineering, or a related field, or equivalent practical experience
Snowflake SnowPro Core or Advanced certifications, Apache Spark or Databricks, large data platform migrations, relevant industry knowledge, and Enterprise AI or LLM-based use cases are bonus qualifications