Senior Data Engineer Snowflake Azure Data Factory

Process Global; Hyderabad; On-site; INR 2,800,000 - 4,000,000; Full time

Job summary

Process Global seeks a Senior Data Engineer to design and optimize enterprise data platforms in Hyderabad. You will build scalable Azure and Snowflake solutions, modernize legacy systems and improve reliability for AI/ML-ready data ecosystems.

You will lead technical initiatives, mentor engineers, and collaborate with cross-functional teams to deliver trusted data assets and production-ready pipelines in a fast-paced startup-like environment.

Qualifications

• Bachelor's degree in CS/IT/Engineering.
• 7-10 years of experience in SQL Server & enterprise data engineering.
• Advanced expertise in SQL Server administration & T-SQL.
• Hands-on experience with Azure Data Factory, Azure Synapse Analytics, Azure Data Lake and Snowflake.
• Experience modernizing legacy data platforms and migrating workloads to cloud environments.
• Strong production support, incident management, troubleshooting and root-cause analysis.
• Experience implementing CI/CD, automation, monitoring and DataOps practices.

Responsibilities

• Design, develop and optimize data pipelines using Azure Data Factory and Snowflake.
• Lead migration of legacy SSIS/SSRS workloads to cloud-native platforms.
• Architect scalable solutions for structured, semi-structured and streaming data.
• Implement DataOps, CI/CD pipelines, automation and monitoring.

Skills

SQL Server

T-SQL

Azure Data Factory

Azure Synapse Analytics

Azure Data Lake

Snowflake

Data modelling

Schema design

Query optimization

Performance tuning

Data architecture

CI/CD

DataOps

Leadership

Education

Bachelor's degree in Computer Science / Information Technology / Engineering

Tools

SSIS

SSRS

Job description

Senior Data Engineer Snowflake / Azure Data Factory

Location: Hyderabad, India

Position Summary

The Senior Data Engineer will lead the design, modernization, optimization, and support of enterprise-grade data platforms. This role will focus on building scalable Azure and Snowflake-based data solutions, modernizing legacy systems, strengthening production reliability, and enabling trusted, AI/ML-ready data ecosystems.

The ideal candidate combines deep technical expertise in SQL Server, Azure Data Factory, and Snowflake with strong leadership, production support experience, and the ability to operate effectively in a fast-paced environment.

Key Responsibilities

• Design, develop, and optimize modern data pipelines using Azure Data Factory and Snowflake.
• Lead the migration of legacy SSIS and SSRS workloads to cloud-native data platforms.
• Architect scalable solutions for structured, semi-structured, and streaming data.
• Implement DataOps practices, CI/CD pipelines, automation, monitoring, and deployment controls.
• Ensure data platforms meet performance, scalability, security, availability, and governance requirements.
• Partner with analytics, reporting, and AI/ML teams to deliver trusted and reusable data assets.
• Provide production support for enterprise databases, pipelines, integrations, and reporting environments.
• Perform root-cause analysis and implement preventive solutions for recurring production issues.
• Improve platform reliability, reduce downtime, and strengthen operational monitoring.
• Provide technical leadership and guidance across data modernization initiatives.
• Mentor junior engineers and promote engineering standards, knowledge sharing, and continuous improvement.
• Contribute beyond core technical responsibilities when required in a dynamic, startup-oriented environment.

Required Qualifications

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
• 7-10 years of experience in SQL Server, database administration, and enterprise data engineering.
• Advanced expertise in SQL Server administration and T-SQL.
• Strong hands-on experience with Azure Data Factory, Azure Synapse Analytics, Azure Data Lake, and Snowflake.
• Proven experience in data modelling, schema design, query optimization, performance tuning, and data architecture.
• Experience modernizing legacy data platforms and migrating workloads to cloud environments.
• Strong understanding of production support, incident management, troubleshooting, and root-cause analysis.
• Experience implementing CI/CD, automation, monitoring, and DataOps practices.
• Demonstrated ability to lead technical initiatives and collaborate with cross-functional teams.

Preferred Qualifications

• Experience with streaming technologies such as Apache Kafka or Azure Event Hubs.
• Exposure to AI/ML data platforms and the development of AI-ready data assets.
• Familiarity with data governance, security, lineage, and observability practices.
• Experience working in high-growth, product-driven, or startup environments.