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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 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
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