Snowflake Data Engineer

Role- Snowflake Data Engineer
Client location - NYC, NY
3 days hybrid in a week.
Prefer local to NJ or NY candidates.
Fulltime


We are looking for 10+ years of exp.

Role Overview
Build and scale cloud data products on Snowflake supporting institutional trading, risk, and regulatory reporting. This is a hands-on build role — you will own pipelines end-to-end from ingestion through curated, governed consumption layers used by front-office, risk, and control functions.
Key Responsibilities

• Design, develop, and optimize Snowflake data models (staging → integration → semantic/consumption layers) for institutional trade, position, reference, and market data.
  
• Build ingestion pipelines using Snowpipe / Snowpipe Streaming, Streams & Tasks, Dynamic Tables, and external stages against S3.
  
• Develop transformation logic in SQL and dbt with version control, CI/CD, and automated testing.
  
• Tune performance and cost: warehouse right-sizing, clustering keys, micro-partition pruning, query profiling, result caching, resource monitors, and credit-consumption reporting.
  
• Implement data security and entitlements: RBAC hierarchy, dynamic data masking, row access policies, secure views, and secure data sharing across LOBs.
  
• Migrate legacy Oracle / Teradata / Sybase / Hadoop workloads to Snowflake, including reconciliation and parallel-run validation.
  
• Partner with data governance on lineage, cataloging, data quality rules, and audit/regulatory evidence.
  
• Support production: incident triage, root-cause analysis, SLA adherence, and on-call rotation for critical batch cycles.
  
• Work in Agile squads with BAs, QA, and platform engineering; participate in design reviews and code reviews.
  

Required Qualifications

• 7+ years in data engineering; 4+ years hands-on Snowflake in a production environment.
  
• Expert SQL — window functions, CTEs, complex joins, query optimization, execution plan analysis.
  
•  dbt (Core or Cloud) — models, macros, snapshots, tests, exposures.
  
• Orchestration: Airflow, Control-M, or Autosys.
  
• AWS: S3, IAM, Glue, Lambda, Secrets Manager.
  
• CI/CD and IaC: Git, Jenkins/GitHub Actions, Terraform or Schema change for Snowflake object deployment.
  
• Dimensional and Data Vault modeling; slowly changing dimensions; late-arriving data handling.
  
• Demonstrated Snowflake cost-governance ownership (not just development).
  

Preferred / Differentiators

• SnowPro Core / Advanced Data Engineer certification.
  
• Prior tier-1 investment bank or large financial-services experience.