Hiring- Snowflake Lead (SnowSQL, Snowpark, Snowpipe, Data Modeling)

Pls share your cv to [email protected]

JD - ETL Snowflake Sr. Tech lead- Noida and Bangalore Only

Key Responsibilities

1. Data Pipeline Development

• Design and implement end-to-end CDC-based ingestion pipelines using tools such as Debezium, Fivetran, Qlik Replicate, or StreamSets.
• Develop scalable ELT/ETL pipelines to load structured and semi-structured data into Snowflake.
• Optimize Snowflake performance through clustering, caching, micro-partition tuning, and query optimization.

2. Snowflake Architecture & Modeling

• Build and maintain Snowflake objects: databases, schemas, stages, warehouses, tasks, streams, pipes.
• Implement data modeling best practices (Star/Snowflake schema, Data Vault 2.0, dimensional modeling).
• Manage Snowflake cost optimization and workload management.

3. Data Integration & Streaming

• Integrate data from relational databases (e.g., Oracle, SQL Server, MySQL, PostgreSQL) via CDC.
• Work with streaming platforms like Kafka, Kinesis, or Azure Event Hub (if applicable).
• Implement near real-time ingestion patterns using Snowpipe or Snowflake Streams & Tasks.

4. Data Quality & Governance

• Build data validation, reconciliation, and monitoring frameworks.
• Ensure compliance with data security, privacy, and governance standards.
• Implement role-based access control in Snowflake (RBAC).

5. Collaboration & Documentation

• Partner with Data Architects, Product Owners, and Business Analysts to understand requirements.
• Produce high-quality technical documentation and runbooks.

Required Skills & Experience

Core Technical Skills

• Snowflake (must have): SnowSQL, Snowpark, Snowpipe, Streams & Tasks Performance optimization Data modeling
• CDC Tools (at least one): — Debezium, Fivetran, Qlik Replicate, AWS DMS, HVR, Informatica CDC, StreamSets
• Strong SQL expertise (analytical functions, query tuning).
• Hands-on with one cloud platform: Azure.
• Experience with Python or Scala for ELT/Orchestration.
• CI/CD and orchestration tools (Airflow, Azure Data Factory, GCP Composer, AWS Glue, etc.)