
Senior Data Solutions Architect
4 days ago
About Us
We are a leading technology provider in the meetings and events industry. Our comprehensive event marketing and management platform helps marketers and event professionals grow their business.
Our culture is built on fostering intrapreneurship, where we encourage our team members to think like entrepreneurs and take action. We value diverse perspectives and foster an environment that celebrates differences and shared connections.
The RoleWe are looking for a skilled IT Professional with experience in Snowflake Data Cloud to lead the design, implementation, and optimization of scalable data solutions.
Key Responsibilities:- Architect and deliver end-to-end data solutions on Snowflake.
- Develop deep expertise in Snowflake architecture and apply it to structured, semi-structured, and unstructured data.
- Use Snowflake native load utilities for data ingestion and transformation.
- Develop and manage API-based integrations and automation.
- Lead data governance, quality, security, and compliance efforts.
- Optimize performance and manage costs.
- Oversee Snowflake infrastructure provisioning, scaling, and monitoring.
- Act as primary stakeholder contact and drive meetings to translate business needs.
- Foster innovation in data architecture, analytics, and AI-driven solutions.
- Collaborate with cross-functional teams.
- Stay current on Snowflake advancements, especially AI features like Cortex.
- Proactively perform POCs for new Snowflake features and drive adoptions.
- Leverage data lake frameworks and serverless technologies.
- Bachelor's or master's degree in computer science, IT, or related field.
- 4-12 years of Snowflake Data Cloud experience.
- Deep understanding of Snowflake architecture and ecosystem.
- Strong grasp of data warehousing concepts and diverse data structures.
- Expertise in Snowflake native load utilities.
- API integration and automation experience.
- Data governance, security, and compliance background.
- Performance optimization and cost management skills.
- Experience with Snowflake infrastructure management.
- Excellent communication and stakeholder management.
- Innovative, AI-driven mindset.
- Hands-on Python for data engineering/automation.
- Knowledge of AI, LLMs, and Snowflake AI features.
- Experience with data lake frameworks and serverless technologies.
- Familiarity with data modeling, Python, PySpark, and warehousing best practices.
- Exposure to MLOps, AI/ML pipelines, or deploying AI models.
- Snowflake or relevant cloud certifications.
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