Snowflake Data Engineer

Reuben Cooley; New York (NY); On-site; USD 150,000 - 190,000; Full time

Job summary

Reuben Cooley is seeking a senior data engineer to build and scale cloud data products on Snowflake, owning end-to-end pipelines from ingestion to consumption for front-office, risk, and regulatory reporting.

You will design Snowflake data models, develop transformations in SQL and dbt, implement data security, migrate legacy workloads, and partner with governance on lineage and data quality.

Qualifications

• 7+ years in data engineering or related field.
• 4+ years hands-on Snowflake in production.

Responsibilities

• Design, develop, and optimize Snowflake data models for multiple data domains.
• Build ingestion pipelines using Snowpipe, Streams & Tasks, and external stages against S3.
• Develop transformations in SQL and dbt with version control, CI/CD, and automated testing.
• Tune performance and cost: clustering, pruning, query profiling, and resource monitoring.
• Implement data security and entitlements: RBAC, dynamic masking, and secure views.
• Migrate legacy workloads to Snowflake and collaborate on lineage with governance.

Skills

SQL proficiency

Data modeling

Performance tuning

Data governance

Tools

Snowflake

dbt

Airflow

AWS S3

CI/CD

Terraform

Control-M

Autosys

Job description

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.

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.

Qualifications

• 7+ years in data engineering; 4+ years hands-on Snowflake in a production environment.

Required Skills

• 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.