YOUR ROLE
Practice: Data Engineering & Architecture
We are looking for a highly skilled Snowflake Hands-on Architect who can seamlessly bridge strategic architecture and hands-on development. This role requires someone who is equally comfortable leading technical design discussions with stakeholders, defining enterprise data architecture, and actively contributing to implementation through advanced SQL development, performance tuning, and platform optimization.
As a Hands-on Architect, you will be responsible for designing, governing, and scaling the Snowflake data platform while ensuring that architectural decisions align with business objectives, security requirements, and operational excellence. You will play a key role in establishing best practices for data ingestion, transformation, storage, governance, and consumption across the organization.
This is not a purely advisory role. You will remain closely involved in execution, working alongside engineering teams to build scalable data solutions, optimize workloads, troubleshoot complex challenges, and ensure successful delivery of enterprise-grade data platforms. The ideal candidate combines deep Snowflake expertise with strong architectural vision, leadership capabilities, and a passion for solving complex data engineering challenges.
YOUR PROFILE
Copilot said:
What You'll Do
- Design scalable, secure, and end-to-end data platform solutions on Snowflake, translating business requirements into robust technical architectures.
- Apply deep expertise in Apache Iceberg implementation, performance tuning, and Snowflake Open Storage Integration (OSI) concepts.
- Develop, optimize, and troubleshoot advanced SQL solutions, including complex queries, analytical functions, and performance tuning.
- Architect solutions across Snowflake’s storage, compute, and cloud services layers, leveraging best practices for AWS, Azure, and GCP environments.
- Apply data warehousing and data modeling principles, including Star Schema, Snowflake Schema, Data Lakehouse, Dimensional Modeling, and Data Vault methodologies.
- Design and implement ELT/ETL ingestion pipelines and transformation frameworks using Snowflake capabilities such as Streams, Tasks, Snowpipe, Time Travel, and Zero-Copy Cloning.
- Own workflow orchestration and automation processes, including DAG-based pipeline execution and scheduling.
- Develop custom business logic using Python, Snowpark, and Snowflake stored procedures.
- Drive platform performance optimization and cost management through effective query tuning, warehouse sizing, workload management, and caching strategies.
- Define and enforce enterprise data security and governance standards, including RBAC, data masking, compliance controls, and access management.
- Design and implement data pipelines supporting batch, streaming, CDC (Change Data Capture), and real-time processing, integrating with external systems, ETL tools, streaming platforms, and APIs.
- Serve as the technical bridge between business stakeholders and engineering teams, translating business objectives into scalable architectural solutions.
What We're Looking For
- Strong, proven understanding of Snowflake architecture and cloud-native data platform design principles.
- Demonstrated experience designing and delivering end-to-end, enterprise-scale, production-grade data solutions.
- Deep expertise in data engineering, data modeling, and modern cloud data architectures.
- Strong analytical, troubleshooting, and problem-solving capabilities with the ability to evaluate and balance architectural trade-offs.
- Hands-on experience with performance tuning, scalability planning, security, governance, and cost optimization in Snowflake environments.
- Proficiency in SQL, Python, Snowpark, and modern data integration technologies.
- Excellent communication and stakeholder management skills, with the ability to navigate both business and technical discussions effectively.
- A collaborative, hands-on mindset with the ability to lead by example and drive technical excellence across teams.