Principal Data Architect
Model NSalary not specified
- Full Time
- Expert & Leadership (9+ years)
Not SpecifiedCompensation
Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
AI & Machine Learning, Enterprise Software, Data & AnalyticsIndustries
Requirements
Candidates should have over 10 years of experience in data architecture, data engineering, or solution architecture roles. Deep expertise in Azure cloud services, including Azure Data Lake Storage, Azure Synapse, and Azure Fabric is required, along with strong hands-on experience with Databricks. A proven track record in designing and implementing Lakehouse architectures for large-scale enterprise customers is essential. Candidates must also possess expertise in SQL, Python, and ETL/ELT frameworks for data transformation and analytics, as well as a strong understanding of data governance, security, and compliance best practices in the cloud. Excellent communication and stakeholder management skills are necessary, with the ability to translate technical concepts into business value. Experience in customer-facing roles such as pre-sales, consulting, or customer success is a plus.
Responsibilities
The Platform Architect will engage with enterprise customers to architect scalable, high-performance, and cost-efficient data solutions leveraging Snowflake in conjunction with Azure and Databricks. They will design and optimize data architectures based on Lakehouse principles, guiding customers on best practices for data ingestion, transformation, and analytics. The role involves leading technical discussions and delivering compelling presentations, demonstrations, and proofs-of-concept showcasing Snowflake’s value proposition. Collaboration with internal teams, including Sales, Product, and Engineering, is necessary to align solutions with customer needs and Snowflake’s roadmap. Additionally, the architect will advocate for Snowflake’s ecosystem by articulating integration patterns with Azure services and Databricks, stay ahead of industry trends, and provide thought leadership on cloud data management, data engineering, and AI/ML enablement. They will also educate and enable customers on migration strategies from legacy data warehouses and competing cloud platforms to Snowflake.
Skills
SQL
Python
Azure Data Lake Storage
Azure Synapse
Azure Fabric
Databricks
Unity Catalog
Delta Lake
Spark
MLflow
ETL
ELT
Data Governance
Data Security
Snowflake
Data management and analytics platform
About Snowflake
Snowflake provides a platform called the AI Data Cloud that helps organizations manage and analyze their data. This platform allows users to store and process large amounts of data efficiently, offering services like data warehousing, data lakes, data engineering, data science, and data sharing. Snowflake's system works by uniting data from different sources, enabling secure sharing and performing various types of analytics. What sets Snowflake apart from its competitors is its ability to operate seamlessly across multiple public clouds, allowing users to access their data from anywhere. The company's goal is to help businesses leverage their data for better decision-making by providing a flexible subscription-based service that scales according to their needs.
Bellevue, WashingtonHeadquarters
2012Year Founded
$1,341.3MTotal Funding
IPOCompany Stage
Data & Analytics, Enterprise Software, AI & Machine LearningIndustries
5,001-10,000Employees