Overview

Senior Snowflake Data Engineer

Responsibilities

• Design, develop, and maintain scalable data warehouse solutions in Snowflake, including databases, schemas, tables, views, secure views, streams, tasks, stages, file formats, and data sharing patterns.dbt Development and Transformation: Build, test, document, and maintain dbt models, macros, snapshots, seeds, sources, exposures, and reusable transformation logic following modular, version-controlled, and production-ready engineering practices.
• Design dimensional, normalized, and analytics-ready data models, including staging, intermediate, mart, fact, and dimension layers aligned with business reporting requirements and data governance standards.
• Optimize Snowflake queries, clustering strategies, warehouse sizing, compute usage, query profiles, caching behavior, storage design, and workload patterns to improve performance, reliability, and cost efficiency.

Qualifications

• 1015+ years of
• experience in data engineering, data warehousing, analytics engineering, or similar roles, with strong experience delivering production-grade cloud data warehouse solutions.
• In-depth knowledge of Snowflake and dbt is required, including Snowflake architecture, SQL development, warehouse design, role-based access concepts, performance tuning, dbt model development, testing, documentation, lineage, and deployment practices.
• Preferred and Supporting Skills:
• Proficiency with Fivetran for automated data ingestion is required.
• Knowledge of Microsoft SQL Server, T-SQL, stored procedures, indexing, query tuning, SQL Agent jobs, and legacy database integration is strongly preferred.
• Communication and Collaboration:
• Strong communication skills with the ability to work closely with data engineers, analytics engineers, DBAs, architects, analysts, product teams, and business stakeholders to clarify requirements, resolve issues, and deliver trusted data products .