Leads the architecture and engineering of scalable Snowflake data platforms, including ETL pipelines, data warehouses, streaming ingestion, stored procedures, performance optimization, security, and automation. Troubleshoots platform issues, collaborates on enterprise data initiatives, and mentors junior architects and engineers. The role requires deep Snowflake, SQL, Python, data modeling, and modern data platform expertise, with preferred experience in cloud platforms, orchestration tools, governance, and real-time analytics.
Principal Architect
Primary Skills
- DataStream, ETL Fundamentals, SQL, SQL (Basic + Advanced), Python, Data Warehousing, Time Travel and Fail Safe, Snowpipe, SnowSQL, Modern Data Platform Fundamentals, Data Modelling Fundamentals, PLSQL, T-SQL, Stored Procedures
Specialization
- Snowflake Engineering: Principal Data Architect
Job requirements
- Design and architect scalable, secure, and high-performance Snowflake data solutions to drive enterprise data initiatives.
- Develop and implement robust ETL pipelines using Snowflake Streams, Python, and SQL to enable efficient data ingestion and transformation.
- Optimize Snowflake environments for performance, cost, and reliability by leveraging features such as Time Travel, Fail Safe, and Snowpipe.
- Lead the modeling and structuring of complex Snowflake data warehouses, ensuring data integrity, accessibility, and scalability.
- Configure and manage SnowSQL, stored procedures, and advanced SQL scripts to automate data processing and analytics workflows.
- Collaborate with cross-functional teams to define data platform requirements and deliver modern data solutions aligned with business objectives.
- Troubleshoot and resolve architectural and operational issues within Snowflake and related data platforms, ensuring minimal downtime.
- Mentor and guide junior architects and engineers on best practices in Snowflake engineering and data platform fundamentals.
- Expertise in Snowflake architecture and engineering
- Advanced proficiency in SQL
- Strong experience with Python for data processing and automation
- Deep understanding of ETL pipeline development
- Hands-on experience with Snowflake Streams for real-time data ingestion
- Proficiency in Time Travel and Fail Safe features within Snowflake
- Implementation and management of Snowpipe for automated data loading
- Skilled in SnowSQL for scripting and data management
- Experience in Snowflake-specific data modeling and warehouse design
- Expertise in developing and managing Snowflake stored procedures
- Experience integrating Snowflake with cloud platforms such as AWS or Azure
- Expertise in advanced data security and governance practices
- Knowledge of performance tuning and optimization for large-scale Snowflake workloads
- Familiarity with emerging data engineering technologies and frameworks
- Experience with orchestration tools for automating data pipelines (e.g., Apache Airflow, dbt)
- Hands-on experience with real-time analytics and streaming data solutions
- Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a closely related discipline
- Snowflake SnowPro Advanced Architect certification or equivalent
- Certification in data warehousing or cloud data platform architecture (e.g., AWS Certified Data Analytics, Microsoft Certified: Azure Data Engineer Associate)
15 to 18 years of experience in data architecture and engineering, including extensive expertise in Snowflake and modern data platforms
Key Responsibilities:
Required Skills:
Preferred Skills:
Desired Qualifications:
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