Role Snowflake Architect
Job Summary -
As a Data Architect, you are core to the D&AI (Data & AI) Practices success. Data is foundational to everything we do, and you are accountable for defining and delivering best-in-class Snowflake data management solutions across all major cloud platforms. This is a senior role with high visibility and reporting to the D&AI Practice Tower Lead.
Job Responsibilities
Architectural Design: Architect secure, scalable, highly performant data engineering and management solutions, including data warehouses, data lake, ELT / ETL and real-time data engineering / pipeline solutions. Support Principal Data Architect in defining and maintaining Practice reference data engineering and data management architectures.
Snowflake Implementation: Design and manage scalable end-to-end data solutions leveraging native Snowflake workloads including : Data Engineering; Data Lake; Data Warehouse; Applications; Unistore; AI/ML; Governed Collaboration, Marketplace, Streamlit.
Hyperscaler Design: Competently leverage data-related cloud platform (AWS or Azure) capabilities to architect and develop end-to-end data engineering and data management solutions.
Client Engagement: Regular collaboration and partnership with clients to understand their challenges and needs then translate requirements into data solutions that drive customer value. Support proposal development.
Data Modeling: Create and maintain conceptual, logical, and physical data models that support both transactional and analytical needs. Ensure data models are optimized for performance and scalability.
Creativity: Be an out-of-the-box thinker and passionate about applying your skills to new and existing solutions alike while always demonstrating a customer-first mentality.
Mandatory Skills
- 12+ years hands-on data solution architecture and implementation experience on modern cloud platforms (AWS preferred) including microservice and event-driven architectures.
- Snowflake SnowPro Advanced Architect certification. An architectural certification on either AWS, Azure or GCP.
- Hands-on experience with Snowflake capabilities including Snowpipe, Snowpark, Cortex, Polaris Catalog, native applications, Notebooks, Horizon, Marketplace, Streamlit.
- Practical experience with end-to-end data engineering and data management supporting functions including data modeling (conceptual, logical & physical), BI & analytics, data governance, data quality, data security / privacy / compliance, IAM, performance optimization. Advanced SQL and data profiling.
- Python, Scala or Java. Strong communication skills with the ability to convey technical concepts to non-technical users.
- Strong, self-management skills demonstrating ability to multitask and self-manage goals and activities.
Additional / Nice-to-have Qualifications-
Snowflake SnowPro Advanced Data Engineer certification Snowflake SnowPro Advanced Data Scientist certification Snowflake SnowPro Advanced Administrator certification Snowflake SnowPro Advanced Data Analyst certification
Required Education Master or Bachelor (CS, IT, Applied Mathematics or demonstrated experience)