What are the responsibilities and job description for the Snowflake Data Engineer position at Opulent Global Technologies Inc.?
Role: Snowflake Data Engineer
Location :- NY & NJ (Hybrid)
Position Type: Fulltime- No Contract
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.
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).