Sr. Data Engineer

SpinTheory; Hyderabad; On-site; INR 111,600 - 167,400; Full time

Job summary

A leading tech company in Hyderabad, India is seeking a Senior Data Engineer to lead the design and optimization of enterprise data platforms. Responsibilities include modernizing legacy systems, building scalable data pipelines using Azure and Snowflake, and implementing DataOps practices. The ideal candidate will have strong production support expertise and mentor junior engineers, contributing to a dynamic startup environment. This position promises opportunities for innovation and advancement.

Qualifications

• Experience in designing and building modern data pipelines.
• Strong understanding of Azure Data Factory and Snowflake.
• Familiarity with DataOps practices and CI/CD implementation.

Responsibilities

• Lead design and build of data pipelines using Azure and Snowflake.
• Migrate legacy systems to cloud-native solutions.
• Ensure scalability and performance of databases and pipelines.
• Mentor junior engineers and provide production support.

Skills

Data pipeline design

Azure Data Factory

Snowflake

DataOps practices

CI/CD pipelines

Database performance optimization

Mentoring

Job description

The Senior Data Engineer will lead the design, optimization, and support of enterprise-grade, high-availability data platforms. This role is responsible for modernizing legacy systems, building scalable Azure and Snowflake-based pipelines, and enabling AI/ML-ready data ecosystems. The ideal candidate will combine strong production support expertise with a forward-looking mindset to architect and deliver future-ready data platforms. This position is based in Hyderabad, India.

• Design and build modern data pipelines using Azure Data Factory and Snowflake.
• Migrate and modernize legacy SSIS/SSRS workloads to cloud-native solutions.
• Implement DataOps practices, CI/CD pipelines, and automation.
• Ensure database and pipeline scalability, security, and performance.
• Partner with analytics and AI teams to deliver trusted, AI-ready data assets.
• Lead cloud migration initiatives across structured, semi-structured, and streaming data sources.
• Mentor junior engineers, fostering a culture of continuous learning and adaptability.
• Provide production support for enterprise data platforms, including database environments, pipelines and integrations.
• Provide root-cause analysis and preventive solutions for recurring production issues, minimizing downtime and improving stability.
• Contribute beyond technical scope when necessary, demonstrating versatility in a startup environment.