Hiring For Snowflake Lead - Mumbai

Key Responsibilities

1 Data Engineering & Architecture

• Design scalable ELT pipelines using Snowflake + DBT
• Build enterprise-grade data warehouse solutions (Star/Snowflake schema)
• Implement incremental pipelines, CDC workflows, and transformation frameworks
• Drive end-to-end data lifecycle (ingestion transformation serving layer)

2 Snowflake Platform Engineering

• Design and manage:
• Tables, views, schemas
• External/internal stages
• Streams & Tasks (CDC processing)
• Snowpipe (real-time ingestion)
• Optimize:
• Query performance
• Warehouse sizing / scaling
• Clustering & partitioning
• Implement:
• Data security (RBAC, masking policies)
• Data governance & auditing (Time Travel, cloning)

3 DBT (MANDATORY CORE RESPONSIBILITY)

• Build and manage:
• dbt models (staging intermediate marts)
• Incremental models & SCD Type 1/2
• Snapshots & historized datasets
• Implement:
• Data testing (generic + custom)
• Source freshness checks
• Documentation & lineage
• Drive:
• CI/CD pipelines for dbt deployments
• Code modularity & reusability
• Transformation layer governance

4 Orchestration & Integration

• Orchestrate workflows using:
• Airflow / Azure Data Factory
• Integrate data from:
• APIs
• Databases
• Cloud storage (S3 / ADLS)
• Implement:
• Monitoring & alerting
• Data quality frameworks
• Error handling and recovery

5 Leadership & Stakeholder Management

• Lead and mentor data engineering team (36 engineers)
• Own architecture decisions and delivery ownership
• Collaborate with:
• Data Analysts
• Business stakeholders
• Product & Analytics teams
• Drive:
• Best practices
• Code reviews
• Delivery timelines

Required Skills & Experience

Must-Have Skills (STRICT)

• 7+ years of Data Engineering experience
• Expert-level experience in:
• Snowflake (Streams, Tasks, Snowpipe, performance tuning)
• DBT (MANDATORY – strong hands-on experience)
• Strong SQL & data modelling skills
• Experience building ELT pipelines at scale
• Experience with ADF / Airflow / orchestration tools

Good-to-Have

• Kafka / Streaming pipelines
• CI/CD tools (Azure DevOps, GitHub Actions)
• Data governance tools
• Data migration - Legacy Data warehouse/Data Lake to Cloud/Snowflake