Sr Cloud Data Engineer

About the role

Job Title: Senior Cloud Data Engineer
Experience: 5+ Years
Employment Type: Full-Time

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.

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.

Required QualificationsEducation

• 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 SkillsCloud Data Engineering

Strong hands-on experience with:

• Microsoft Azure Cloud
• Azure Data Factory (ADF)
• Self-hosted Integration Runtime (SHIR)
• Azure Data Lake Storage Gen2 (ADLS Gen2)
• Azure Blob Storage
• Azure Logic Apps
• Azure Databricks

Data Platforms

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

ETL/ELT Development

Strong experience with:

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

Programming & Scripting

Experience with:

• Python
• SQL
• Scripting for data processing and automation

DevOps & CI/CD

Experience with:

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

Data Engineering Practices

Strong understanding of:

• 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
• Data Governance
• Problem Solving
• Analytical Thinking
• Technical Leadership
• Collaboration & Communication

Role Outcomes

The successful candidate will:

• Modernize legacy data platforms through successful cloud migration.
• Build scalable and reliable Azure-based data solutions.
• Enable advanced analytics through Snowflake and Databricks platforms.
• Improve data processing efficiency through automation and optimization.
• Establish robust engineering practices supporting enterprise data transformation initiatives.

Work Location: Hybrid remote in Noida, Uttar Pradesh (Noida)

What you'll do

• Own delivery for client-facing web, mobile, AI, cloud or digital transformation work based on the role.
• Collaborate with project managers, designers, QA and client stakeholders through discovery, build, launch and support.
• Write clear documentation, communicate risks early and keep delivery quality high.
• Contribute to reusable engineering practices, reviews and mentoring inside the WebSenor team.

What we're looking for

• Strong hands-on experience relevant to this role and a portfolio of shipped production work.
• Clear communication, ownership mindset and ability to work with global clients.
• Comfort with delivery discipline: estimation, reviews, testing, documentation and release readiness.
• Ability to learn fast and work across modern product, engineering and AI-enabled workflows.

What you'll get

• Work on real enterprise client projects with measurable business outcomes.
• Collaborate with experienced engineering, design, QA and delivery teams.
• Growth through mentoring, project ownership and exposure to global clients.
• HR-approved compensation, benefits and policies as finalized during the offer process.

About the team

You will work with WebSenor project managers, UI/UX designers, QA engineers, cloud specialists and senior developers focused on quality delivery for enterprise clients.

Our hiring process

• Application Review: HR and delivery leadership review your profile for role fit.
• Technical Discussion: Meet the technical team for skill, communication and project-readiness evaluation.
• Final Conversation: Discuss compensation, joining timeline and team fit.
• Offer and Onboarding: Receive the offer, documentation checklist and onboarding plan.