Snowflake Architect

Role Overview: As a Snowflake Architect at NTT DATA, you will lead the design and implementation of enterprise-grade data platforms using Snowflake. Your role will involve defining architectural standards, guiding engineering teams, and collaborating with stakeholders to align data strategies with business goals. You will focus on leveraging Snowflake's advanced capabilities to build scalable, secure, and high-performance data solutions that support analytics, reporting, and data science initiatives. Key Responsibilities: - Define and own the end-to-end architecture of data platforms built on Snowflake, including ingestion, transformation, storage, and consumption layers. - Design and implement data lakehouse architectures using Snowflake's native features such as Streams, Tasks, Materialized Views, and External Tables. - Establish best practices for data governance, security, and access control using Role-Based Access Control (RBAC), Secure Views, and Row-Level Security. - Architect scalable ETL/ELT pipelines using Snowflake, DBT, and Python, integrating with orchestration tools like Airflow. - Lead integration of Snowflake with enterprise systems such as data catalogs, data quality frameworks, monitoring tools, and BI platforms. - Work on AI integrations with Snowflake, including Snowflake Cortex and LLM-powered analytics, enabling intelligent data applications. - Utilize Snowflake Horizon for governance capabilities such as object tagging, data lineage, Data Clean Rooms, and AI-powered object insights. - Guide teams in implementing CI/CD pipelines for Snowflake deployments using tools like GitHub Actions, Azure DevOps, or GitLab CI. - Monitor and optimize Snowflake performance using Query Profile, Resource Monitors, Clustering Keys, and Auto-Suspend/Resume features. - Collaborate with data analysts, engineers, and business stakeholders to ensure platform reliability and data accessibility. - Conduct architectural reviews, code audits, and mentoring sessions to ensure adherence to standards and scalability. - Stay current with Snowflake innovations and advocate for adoption of new features and capabilities. Qualifications Required: - Bachelor's degree in Computer Science, Software Engineering, Information Technology, or related field required. - Minimum 10 years of experience in data development and solutions in highly complex data environments with large data volumes. - Minimum 10 years of SQL / PLSQL experience with the ability to write ad-hoc and complex queries for data analysis. - Minimum 7 years of experience developing data pipelines and data warehousing solutions using Python and libraries such as Pandas, NumPy. - Familiarity with Snowflake's architecture, virtual warehouses, data storage layers, and compute scaling. - Hands-on experience with DBT preferred. - Experience in performance tuning SQL queries, Spark jobs, and stored procedures. - Understanding of E-R data models (conceptual, logical, and physical). - Strong analytical skills, communication skills, and problem-solving skills. (Note: No additional company details were provided in the job description),