Snowflake Lead / Architect

Responsibilities

Define and own the end-to-end data architecture for Snowflake-based data warehousing and analytics solutions, aligned with enterprise standards and best practices.

Design scalable data models, schemas, and data pipelines to support reporting, self-service analytics, and AI/ML workloads.

Architect and oversee the implementation of ELT/ETL frameworks, data ingestion patterns, and integration with diverse source systems (batch and real-time).

Lead modernization of legacy data warehouses to Snowflake, including migration strategy, performance optimization, and cost management.

Establish data automation strategies, including orchestration, monitoring, and CI/CD for data pipelines and data products.

Collaborate with AI/ML teams to design data platforms that support feature stores, model training, and model inference at scale.

Define and implement data governance, data quality, security, and access control frameworks within Snowflake and related tools.

Provide architectural guidance and technical leadership to data engineers, developers, and analysts across projects.

Conduct architecture reviews, PoCs, and technology evaluations for data engineering, automation, and AI-enabling tools and platforms.

Optimize Snowflake performance, storage, and compute usage through clustering, partitioning, caching, and workload management.

Develop and maintain architecture blueprints, reference implementations, and reusable patterns for data warehousing and analytics.

Partner with product owners and business stakeholders to translate analytical and AI requirements into robust data solutions.

Ensure solutions are secure, compliant, resilient, and aligned with organizational policies and regulatory requirements.

Mentor and upskill team members on Snowflake, data engineering best practices, and data automation techniques.