Key Responsibilities

- Snowflake Data Warehouse Development:

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.

- Fivetran Data Ingestion:

Configure, monitor, and support Fivetran connectors for source system ingestion, schema drift handling, data freshness monitoring, connector troubleshooting, and integration with Snowflake landing and staging layers.

- Data Modeling and Warehouse Design:

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.

- Snowflake Performance and Cost Optimization:

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.

- Production Support and Data Quality:

Troubleshoot pipeline failures, data discrepancies,



dbt test failures, Fivetran sync issues, Snowflake access or performance issues, and implement automated validation, reconciliation, monitoring, and alerting processes.

Qualifications

- Experience:

10–15+ years of hands-on experience in data engineering, data warehousing, analytics engineering, or similar roles, with strong experience delivering production-grade cloud data warehouse solutions.

- Required Technical Skills:

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:

Solid 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

📌 Senior Snowflake Data Engineer (Panchkula)
🏢 Adecco
📍 Panchkula