Snowflake Architect

U3 INFOTECH PTE. LTD.; Singapore; On-site; SGD 70,000 - 100,000; Full time

Job summary

U3 INFOTECH PTE. LTD. is seeking a data engineering expert to design and implement Snowflake-based data architectures and scalable data models.

You will build and optimize ETL/ELT pipelines with Python and advanced SQL, and orchestrate workflows using dbt and Airflow across cloud platforms. You will deploy data solutions on AWS/Azure/GCP, establish CI/CD with Git, ensure data quality, governance and security, and craft GenAI-ready architectures including RAG and AI agents that securely interact

Qualifications

• Proficient in Python and advanced SQL for building pipelines.
• Experience designing Snowflake-based data architectures.
• Strong skills in ETL/ELT pipelines and data modeling.
• Knowledge of dbt, Airflow, and CI/CD practices.
• Familiar with cloud platforms (AWS/Azure/GCP) and data governance.

Responsibilities

• Design and implement Snowflake-based data architecture and models.
• Build and optimise ETL/ELT data pipelines using Python and advanced SQL.
• Orchestrate workflows with dbt and Airflow or equivalent.
• Deploy and manage data solutions on AWS, Azure or GCP.
• Set up CI/CD and version control using Git.
• Enforce data quality, governance and security standards.
• Build GenAI-ready data architecture, including RAG and AI agents that interact securely with enterprise data.

Skills

Python

Advanced SQL

Data pipelines / ETL / ELT

Snowflake

Data modeling

dbt

Airflow or equivalent

Cloud: AWS, Azure or GCP

Git and CI/CD

Data quality and governance

Tools

Spark / PySpark

Kafka / streaming

Iceberg / Delta Lake

Docker / Kubernetes

Data observability

Semantic layer

Cost and performance optimisation

Job description

Key responsibilities

• Design and implement Snowflake-based data architecture and data models
• Build and optimise data pipelines (ETL/ELT) using Python and advanced SQL
• Orchestrate workflows with dbt and Airflow or an equivalent tool
• Deploy and manage data solutions on AWS, Azure or GCP
• Set up CI/CD and version control using Git
• Enforce data quality, governance and security standards
• Build GenAI-ready data architecture, including RAG and AI agents that interact securely with enterprise data

Must-have skills

• Python
• Advanced SQL
• Data pipelines / ETL / ELT
• Snowflake
• Data modeling
• dbt
• Airflow or equivalent
• Cloud: AWS, Azure or GCP
• Git and CI/CD
• Data quality and governance

Good to have

• Spark / PySpark
• Kafka / streaming
• Iceberg / Delta Lake
• Docker / Kubernetes
• Data observability
• Semantic layer
• Cost and performance optimisation

GenAI exposure

• RAG
• AI agents
• MCP
• GenAI-ready data architecture
• Building agents that securely interact with enterprise data