S

Snowflake

Runs a cloud platform for business data and AI

Technical Architect - Frontier Engineering

Implementation & Technical Account ManagementPosted on Nov 11
Full-timeSingaporeNo salary listed

About the Job

Requirements

  • At least 5 years of experience in a customer-facing technical role such as consulting, data engineering, or solutions architecture, and at least 8 years of overall technology experience.
  • Strong hands-on skills in SQL and Python for 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.
  • A degree in computer science, engineering, or a related field, or equivalent practical experience.
  • Ability to travel to customer sites within the region as needed.

Responsibilities

  • 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 Snowflake features including Openflow, dbt projects on Snowflake, Snowpipe, Streams and Tasks, Dynamic Tables, and Snowpark with Python, Java, or Scala.
  • 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 to productionize secure, containerized workflows and interactive UI tools.
  • Help customers adopt Snowflake Cortex AI features, such as Cortex AISQL functions, Cortex Search, Cortex Analyst, and CoCo, to bring AI to their data; deploy ML Ops.
  • Set up automated deployment, such as 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.

Desired Qualifications

  • Snowflake SnowPro Core or Advanced certifications.
  • Experience with Apache Spark or Databricks.
  • Delivery experience on large data platform migrations.
  • Industry knowledge in financial services, telecommunications, retail, or the public sector.
  • Hands-on experience with enterprise AI or LLM-based use cases.

About the Company

Snowflake

Runs a cloud platform for business data and AI

Snowflake runs a cloud platform where businesses store and analyze data, build AI tools, and share information under common access controls. Its platform separates stored data from computing resources, letting teams run different workloads without maintaining database servers. Analysts query business records with SQL, while developers use Python and other languages to build applications and train models against the same data; Cortex connects AI models to company records so teams build assistants and automate analysis. Customers pay for storage and computing usage across Amazon, Microsoft, and Google infrastructure. Snowflake was founded in 2012 and has its headquarters in Menlo Park, California.

Company size
10,001+
Company stage
IPO
Headquarters
Menlo Park, CA
Founded
2012

Recently Posted Jobs

Explore more opportunities at Snowflake

See more jobs