Snowflake Developer

Min Experience: 5+ years

Location: Pune, Maharashtra, India, Bengaluru, Karnataka, India

JobType: full-time

• →Design and develop scalable data pipelines and modern data architectures using Snowflake.
• →Lead migration initiatives from legacy databases to Snowflake.
• →Build and optimize ELT frameworks using DBT.
• →Develop and orchestrate workflows using Apache Airflow.
• →Design and implement data models, including Star Schema and Snowflake Schema.
• →Develop ingestion pipelines for structured and semi-structured data.
• →Create reusable frameworks for data validation, reconciliation, auditing, and monitoring.
• →Optimize Snowflake objects, including: 
• →Virtual Warehouses
• →Clustering Keys
• →Materialized Views
• →Streams & Tasks
• →Dynamic Tables
• →Develop technical design documents and migration runbooks.
• →Perform code reviews and enforce engineering best practices.

• →Assess and migrate data from legacy platforms, including: 
• →Oracle
• →SQL Server
• →Teradata
• →Netezza
• →DB2
• →SAP HANA
• →On-Prem Data Warehouses
• →Perform source system analysis and database rationalization.
• →Design migration strategies, including: 
• →Full Data Loads
• →Incremental Loads
• →CDC (Change Data Capture)
• →Historical Data Migration
• →Conduct data reconciliation and validation during migration.
• →Optimize transformed workloads for Snowflake architecture.
• →Execute cutover planning and post-migration stabilization.

• →Provide L3 support for Snowflake data platforms and pipelines.
• →Monitor and manage production data workloads.
• →Troubleshoot data failures, performance issues, and pipeline disruptions.
• →Perform root cause analysis (RCA) and implement permanent fixes.
• →Support incident, problem, change, and release management activities.
• →Work closely with business users and stakeholders to resolve production issues.
• →Ensure adherence to SLA and operational support commitments.
• →Participate in production releases and deployment activities.

Snowflake, DBT, Airflow

Informatica, SQL, Datastage