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TI

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

Tranzeal Inc.
🇮🇳 India
On-site
Senior
5 months ago
  • Snowflake
  • RBAC
  • SQL
  • Azure Data Factory
  • Azure Functions
  • ETL
  • ELT
  • Python
  • C#
  • Terraform
  • Bicep
  • dbt
  • Azure
5 months ago
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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.

Senior Data Engineers (Snowflake , ADF , ETL ,Python , Data Model) · Tranzeal Inc.

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