Project Role : Data Platform Engineer
Project Role Description : Assists with the data platform blueprint and design, encompassing the relevant data platform components. Collaborates with the Integration Architects and Data Architects to ensure cohesive integration between systems and data models.
Must have skills : Snowflake Data Warehouse
Good to have skills : NA
Minimum 12 Year(s) Of Experience Is Required
Educational Qualification : 15 years full time education
Summary:
As a Data Platform Engineer, you will assist with the data platform blueprint and design, encompassing the relevant data platform components. Your typical day will involve collaborating with Integration Architects and Data Architects to ensure cohesive integration between systems and data models, while also engaging in discussions to refine and enhance the overall data architecture strategy. You will be involved in various stages of the data platform lifecycle, ensuring that all components work harmoniously to support the organization's data needs and objectives.
Job Title: Snowflake Architect with Generative AI Experience – Exec Level
AI Powered Tech Talent
Key Responsibilities:
Snowflake Architecture & Engineering:
Design and implement Snowflake solutions across data ingestion, storage, transformation, and access.
Create and maintain reference architectures, accelerators, design patterns, and solution blueprints.
Track and evangelize Snowflake's latest features and assess their potential for client impact.
Lead capability growth initiatives by mentoring team members, driving POCs, and contributing to knowledge repositories.
Provide solutioning support, including proposal creation, estimations, and client presentations.
Develop performance-optimized pipelines using Snowflake-native capabilities and modern ELT tools (e.g., DBT, Airflow, Fivetran).
Establish data governance, security models, RBAC, and masking policies in line with compliance standards (e.g., SOC2, HIPAA, GDPR).
GenAI:
Collaborate with AI/ML teams to enable GenAI use cases leveraging Snowflake s native capabilities.
Stay abreast of evolving Snowflake & GenAI capabilities recommend and pilot new frameworks.
Integrate Cortex AI to build semantic search over unstructured and structured data.
Lead the development and deployment of Cortex-AI, including defining multi-modal responses.
Required Qualifications and Certifications:
12 years of experience as a Snowflake Architect, Data Engineer, or similar role.
Strong command of Snowflake internals, including performance tuning, clustering, caching, cost optimization.
Strong knowledge of SQL, Snowflake scripting, and any one cloud platforms (AWS, Azure, or GCP).
Experience building or integrating Generative AI applications and experience with Snowflake Cortex.
Familiarity with Snowpark, Python, DBT, Fivetran, Streamlit.
Knowledge of Advanced Features like dynamic tables, Snowpipe streaming, SPCS, authentication etc.
Strong communication and architecture skills with the ability to bridge technical & business discussions.
SnowPro Core & SnowPro Advanced Architect Certification.
Education Qualification:
- 15 years full time education is required.
