Senior Data Engineers (Snowflake, ADF, ETL,Python, Data Model)

Required Qualifications: Budget: 22-24 LPA Location: Any Cognizant office - Hybrid " 4 5 years of experience as a Data Engineer. " Expertise in Snowflake including architecture, RBAC, warehouses, micro-partitioning, query tuning, Snowpipe, Streams & Tasks. " Strong proficiency in complex SQL including CTEs, window functions, and optimization. " Experience building data pipelines in Azure Data Factory. " Working knowledge of Azure Functions including triggers, logging, monitoring, and scaling. " Experience designing scalable, reliable ETL/ELT pipelines. Preferred Qualifications " Proficiency in Python for transformation and automation. " Understanding of C# (especially for Azure Functions). " Experience with event-driven or streaming architectures using Event Hub, Service Bus, or Kafka-like patterns. " Familiarity with Terraform, Bicep, or ARM templates. " Experience with dbt or SQL-based transformation frameworks. " Experience with observability, alerting, and monitoring for data systems. Streaming & Real-Time Data Engineering " Experience with Snowpipe Streaming for sub-minute ingestion. " Implementing CDC patterns using Streams & Tasks. " Real-time ingestion from Azure Event Hub or Service Bus into Snowflake. " Managing schema drift, late-arriving data, and idempotent processing. " Optimizing real-time queries and incremental models. Cost Optimization Expertise Snowflake Cost Optimization: " Warehouse right-sizing and workload pattern tuning. " Using auto-suspend/resume effectively. " Reducing scan volume via pruning and clustering. " Monitoring Time Travel/Fail-safe retention and storage. " Query optimization for efficient compute usage. " Using resource monitors to prevent runaway costs. Azure Cost Optimization: " Designing efficient ADF pipelines minimizing compute and run time. " Optimizing Azure Functions execution time and memory. " Reducing unnecessary data movement. " Leveraging Azure Cost Management for monitoring and forecasting. Required Qualifications: Budget: 22-24 LPA Location: Any Cognizant office - Hybrid " 4 5 years of experience as a Data Engineer. " Expertise in Snowflake including architecture, RBAC, warehouses, micro-partitioning, query tuning, Snowpipe, Streams & Tasks. " Strong proficiency in complex SQL including CTEs, window functions, and optimization. " Experience building data pipelines in Azure Data Factory. " Working knowledge of Azure Functions including triggers, logging, monitoring, and scaling. " Experience designing scalable, reliable ETL/ELT pipelines. Preferred Qualifications " Proficiency in Python for transformation and automation. " Understanding of C# (especially for Azure Functions). " Experience with event-driven or streaming architectures using Event Hub, Service Bus, or Kafka-like patterns. " Familiarity with Terraform, Bicep, or ARM templates. " Experience with dbt or SQL-based transformation frameworks. " Experience with observability, alerting, and monitoring for data systems. Streaming & Real-Time Data Engineering " Experience with Snowpipe Streaming for sub-minute ingestion. " Implementing CDC patterns using Streams & Tasks. " Real-time ingestion from Azure Event Hub or Service Bus into Snowflake. " Managing schema drift, late-arriving data, and idempotent processing. " Optimizing real-time queries and incremental models. Cost Optimization Expertise Snowflake Cost Optimization: " Warehouse right-sizing and workload pattern tuning. " Using auto-suspend/resume effectively. " Reducing scan volume via pruning and clustering. " Monitoring Time Travel/Fail-safe retention and storage. " Query optimization for efficient compute usage. " Using resource monitors to prevent runaway costs. Azure Cost Optimization: " Designing efficient ADF pipelines minimizing compute and run time. " Optimizing Azure Functions execution time and memory. " Reducing unnecessary data movement. " Leveraging Azure Cost Management for monitoring and forecasting.