
Senior Data Solutions Architect
2 weeks ago
Cvent is a leading provider of meetings, events, and hospitality technology. With over 4,800 employees and more than 22,000 customers worldwide, our platform delivers comprehensive event marketing and management solutions for marketers and event professionals.
Our culture fosters innovation, encouraging our people to think and act like entrepreneurs. We value diversity and celebrate individual perspectives, ensuring that our culture promotes shared connections among colleagues and clients.
About the Role:
- We are seeking an IT professional with experience in designing, implementing, and optimizing scalable data solutions using Snowflake Data Cloud.
- The ideal candidate excels in Snowflake architecture, data warehousing, data lakes, serverless/cloud automation, and AI/LLM concepts, and has strong leadership skills.
- Key Responsibilities include architecting end-to-end data solutions on Snowflake, demonstrating deep understanding of data warehousing concepts, working with structured, semi-structured, and unstructured data, and applying expertise in Snowflake architecture.
- The role also involves using Snowflake native load utilities for data ingestion and transformation, developing and managing API-based integrations and automation, leading data governance, quality, security, and compliance efforts, and overseeing Snowflake infrastructure provisioning, scaling, and monitoring.
Qualifications:
- Bachelor's/master's in computer science, IT, or related field, with 4-12 years of experience in Snowflake Data Cloud.
- Deep understanding of Snowflake architecture and ecosystem, as well as strong grasp of data warehousing concepts and diverse data structures.
- Expertise in Snowflake native load utilities, API integration and automation, data governance, security, and compliance, performance optimization and cost management skills, experience with Snowflake infrastructure management, and excellent communication and stakeholder management.
Preferred Qualifications:
- Familiarity with data modeling, Python, PySpark, and warehousing best practices, exposure to MLOps, AI/ML pipelines, or deploying AI models, and Snowflake or relevant cloud certifications.
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