Snowflake Technical Architect

Role & responsibilities

Snowflake Technical Architect

Experience: 815 Years
Location: Bangalore
Employment Type: Full-Time

Job Summary

We are seeking an experienced Snowflake Technical Architect with strong expertise in Snowflake Data Warehouse, Data Migration, and Oracle to Snowflake modernization projects. The ideal candidate will be responsible for architecting, designing, and leading enterprise-scale data platform implementations while ensuring scalability, security, and performance optimization.

Key Responsibilities

• Design and implement scalable data warehouse solutions using Snowflake.
• Lead Oracle Database to Snowflake migration initiatives, including assessment, strategy, and execution.
• Define data architecture, data modeling, ETL/ELT frameworks, and best practices.
• Develop and optimize Snowflake objects such as databases, schemas, tables, views, tasks, streams, and stored procedures.
• Collaborate with business stakeholders, data engineers, and application teams to define data solutions.
• Implement performance tuning, cost optimization, security, governance, and access control mechanisms.
• Design and manage data integration pipelines using ETL/ELT tools.
• Provide technical leadership, architecture guidance, and mentoring to development teams.
• Ensure data quality, reliability, and compliance with enterprise standards.

Required Skills

• Strong experience in Snowflake Architecture and Development.
• Proven experience in Oracle Database to Snowflake Migration projects.
• Expertise in SQL, PL/SQL, SnowSQL, and database performance tuning.
• Experience with Data Modeling (Dimensional & Data Vault concepts).
• Knowledge of ETL/ELT tools such as Informatica, Matillion, Talend, or equivalent.
• Experience with cloud platforms such as Azure, AWS, or GCP.
• Understanding of data governance, security, and access management.
• Strong analytical, problem-solving, and stakeholder management skills.

Preferred Skills

• Snowflake Certifications.
• Experience with Python, Spark, or Data Engineering frameworks.
• Knowledge of CI/CD, DevOps, and Agile methodologies.
• Experience in large-scale enterprise data modernization programs.