Snowflake Senior Technical Lead

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), Private Link, 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.

• Fin Ops practices and cost-attribution models for data platforms.
• Observability tools (Prometheus, Grafana, Open Telemetry, Datadog).
• Experience with Docker, Kubernetes, Terraform, and modern CI/CD pipelines

Other Requirements

BS/MS in Computer Science, Engineering, or related field.

Snow Pro Advanced certifications (Architect, Data Engineer, or Administrator).