Data Engineer (Azure Data Factory & Snowflake)

Cognizant is a leading technology company, and they are seeking a Data Engineer to build and improve enterprise data pipelines and models using Azure Data Factory and Snowflake. The role involves designing workflows, optimizing data models, and ensuring data quality and reliability.

Responsibilities:

• Design, develop, and maintain data integration and orchestration workflows in Azure Data Factory (pipelines, datasets, linked services, triggers, parameters, and reusable patterns)
• Build and optimize Snowflake data models (staging/integration layers, dimensional or curated models as needed), including performance tuning and cost-aware warehouse usage
• Implement robust operations across ingestion and transformation: monitoring, alerting, logging, failure handling, retry strategies, and runbook-driven support
• Manage and mitigate schema drift and breaking source changes, partnering with downstream consumers to keep contracts stable
• Ensure data quality and reliability through validation checks, reconciliation, and automated testing where appropriate

Requirements:

• 5+ years of experience in data engineering, analytics engineering, or similar roles delivering production-grade pipelines
• Hands-on experience building and operating pipelines in Azure Data Factory, including parameterized pipelines and multi-environment deployments
• Strong hands-on experience with Snowflake, including SQL development, schema design, and performance tuning
• Strong SQL skills (joins, window functions, CTEs, query optimization) and solid understanding of data warehousing concepts
• Experience with orchestration and operational best practices (scheduling, monitoring, incident response, and root cause analysis) and proficiency with version control (Git)
• Experience implementing metadata-driven frameworks (config-driven job execution, reusable pipeline templates, dynamic parameterization)
• Experience with ELT tooling and Snowflake-native patterns (tasks/streams, Snowpipe, clustering/partitioning concepts, zero-copy cloning)
• Experience with data quality/testing frameworks and automation (unit/integration tests, schema checks, reconciliation)
• Experience with data governance concepts (source-to-target lineage, access controls, PII handling, retention) and cloud security patterns in Azure
• Experience operating Fivetran at scale (multiple connectors, environments, role-based access, connector ownership, and cost management)