Sr Cloud Data Engineer

Job Title: Senior Cloud Data EngineerExperience: 5+ YearsEmployment 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)

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