Job Summary

Role Summary We are seeking a highly skilled Senior Cloud Data Engineer to support a large-scale Cloud Data Modernization initiative. The ideal candidate will have strong experience in migrating enterprise data platforms from on-premises environments to Azure Cloud and Snowflake, along with hands-on expertise in designing, developing, and optimizing modern cloud-based data solutions.

About the role

Job Title: Senior Cloud Data Engineer

Experience: 5+ Years

Employment Type: Full time

We are seeking a highly skilled Senior Cloud Data Engineer to support a large-scale Cloud Data Modernization initiative. The ideal candidate will have strong experience in migrating enterprise data platforms from on-premises environments to Azure Cloud and Snowflake, along with hands-on expertise in designing, developing, and optimizing modern cloud-based data solutions.

The role requires deep technical expertise

The role requires deep technical expertise in Azure Data Services, Databricks, Snowflake, ETL/ELT development, DevOps practices, and data engineering best practices. The successful candidate will collaborate with architects, developers, business teams, and engineering teams to deliver secure, scalable, and high-performing data platforms.

Key Responsibilities

- Lead and execute migration of enterprise ETL workloads from on-premises SQL Server-based data warehouses to Azure Cloud and Snowflake platforms.
- Analyze, redesign, and modernize existing ETL processes developed using SSIS
- T-SQL
- SQL Server-based data workflows
- Design, develop, and implement scalable cloud data engineering solutions using Azure Data Factory (ADF)
- Self-hosted Integration Runtime (SHIR)
- Azure Data Lake Storage Gen2 (ADLS Gen2)
- Azure Blob Storage
- Azure Logic Apps
- Azure Databricks
- Snowflake
- Develop and optimize ETL/ELT pipelines for large-scale data processing and analytics workloads.




- Build data transformation workflows using Databricks and Python-based processing frameworks.
- Implement data ingestion, integration, transformation, and orchestration solutions across enterprise data platforms.
- Configure and manage CI/CD pipelines and DevOps practices using GitHub Actions.
- Collaborate with cross-functional teams including data architects, analysts, application teams, and business stakeholders.
- Troubleshoot data pipeline failures, performance issues, and integration challenges.
- Optimize data workflows for scalability, reliability, and performance.
- Implement security controls, governance practices, and compliance requirements across cloud data platforms.
- Support Agile delivery practices, including sprint planning, technical discussions, code reviews, and release activities.
- Participate in architecture discussions and provide recommendations for cloud data modernization strategies.
- Apply AI/ML capabilities and tools to enhance data processing workflows and ETL automation where applicable.

Qualifications

- Education: Bachelor s degree in Computer Science, Information Technology, Engineering, Data Science, or related field.
- Experience: Minimum 5+ years of experience as a Cloud Data Engineer.
- Strong experience delivering enterprise-scale data engineering solutions.
- Hands-on experience migrating data workloads from on-premises platforms to cloud environments.
- Experience working with modern cloud data architectures and analytics platforms.

Required Technical Skills

- Strong hands-on experience with:




- Microsoft Azure Cloud
- Azure Data Factory
- Self-hosted Integration Runtime
- Azure Data Lake Storage Gen2

Data Platforms

- Databricks
- SQL Server
- Cloud data warehouse concepts
- Data lake and lakehouse architectures

ETL/ELT Development

- ETL pipeline design and development
- SSIS migration and modernization
- T-SQL development
- Data transformation frameworks
- Data ingestion processes
- Data integration patterns

Programming Scripting

- Python
- SQL
- Scripting for data processing and automation

DevOps CI/CD

- GitHub Actions
- CI/CD pipeline implementation
- Source control practices
- Automated deployment processes

Data Engineering Practices

- Data modeling
- Database design principles
- Data quality frameworks
- Data validation
- Performance optimization
- Pipeline monitoring and troubleshooting

Preferred Qualifications

- Experience developing data engineering solutions using Databricks for analytics and large-scale processing workloads.
- Experience with data governance, metadata management, and data quality best practices.
- Knowledge of additional cloud platforms such as AWS
- Google Cloud Platform
- Experience applying AI/ML tools and models to: Data processing workflows
- ETL automation
- Data analytics solutions
- Azure or Snowflake certifications preferred.
- Experience working in Agile/Scrum environments.

Key Competencies

- Cloud Data Engineering
- Azure Data Platform
- Snowflake Development
- Databricks Engineering
- ETL/ELT Modernization
- Data Migration
- Python SQL Development
- Data Pipeline Optimization
- DevOps CI/CD Practices

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Sr Cloud Data Engineer (Noida)
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