Job Summary
Design and build Snowflake optimization capabilities within DCO - warehouse sizing,
query performance, clustering, materialized views, storage tiers, and credit consumption.
• Translate Snowflake expertise into product capabilities - detection rules,
recommendation engines, and safe automated actions for production accounts.
• Build POCs to validate optimization ideas, demonstrate customer value, and support
product discovery and pre-sales.
• Partner with backend, AI/ML, and data engineering teams to ship features end-to-end.
Key Responsibilities
Design and build Snowflake optimization capabilities within DCO - warehouse sizing,
query performance, clustering, materialized views, storage tiers, and credit consumption.
• Translate Snowflake expertise into product capabilities - detection rules,
recommendation engines, and safe automated actions for production accounts.
• Build POCs to validate optimization ideas, demonstrate customer value, and support
product discovery and pre-sales.
• Partner with backend, AI/ML, and data engineering teams to ship features end-to-end.
Skill Requirements
engineering experience; hands-on exp in Snowflake in production.
• Snowflake architecture expertise - three-layer, virtual warehouses, micro-partitions,
clustering/pruning, result/metadata/warehouse caching, time travel, fail-safe, and zerocopy cloning.
• Snowflake platform capabilities - Snowpark, Streams, Tasks, Dynamic Tables,
Materialized Views, Search Optimization Service, Query Acceleration Service, Resource
Monitors, Snowflake Optima, Query Insights, external functions, and SQL API.
• Account administration - RBAC, warehouses, Adaptive Compute, Gen2 Warehouses,
multi-cluster policies, auto-suspend/resume, replication, SnowSQL/REST APIs.
• Advanced query tuning - Query Profile analysis, clustering keys, materialized views,
Search Optimization.
• Cost optimization warehouse right-sizing , credit usage analysis, workload-based
optimization, AISQL / Cortex cost governance (tagging, attribution, budget controls).
• Python (Snowpark), JavaScript/Python UDFs and stored procedures.
• Cloud platforms (AWS / Azure / GCP) - IAM, networking, storage integrations
(S3/ADLS/GCS), PrivateLink, cloud-native Snowflake integrations.
• Strong fundamentals in data structures, algorithms, distributed systems, and large-scale
system design
Snowflake Cortex -Cortex AI Functions (AISQL), AI-driven optimization (intelligent
recommendations, anomaly detection), and native Snowflake automation complementing
optimization logic.
• FinOps practices and cost-attribution models for data platforms.
• Observability tools (Prometheus, Grafana, OpenTelemetry, Datadog).
• Experience with Docker, Kubernetes, Terraform, and modern CI/CD pipelines
Other Requirements
BS/MS in Computer Science, Engineering, or related field.
SnowPro Advanced certifications (Architect, Data Engineer, or Administrator).