Hiring For Snowflake Tech 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 solid hands-on experience) - Strong SQL & data modelling skills - Experience building ELT pipelines at scale - Experience with ADF / Airflow / orch .