Solution Engineer

Job Description :

Andersen is hiring a Solution Engineer in India.

Andersen is an international pre-IPO software development company uniting over 3,500 top-class professionals. For more than 19 years, we have been helping enterprises and middle-sized firms transform their businesses by creating effective digital solutions using innovative technologies.

Today, we are working with businesses from various parts of the world, including Western Europe, the USA, and Asia. Our expertise includes FinTech, Healthcare, Retail, Telecom, Media & Entertainment, Logistics, Travel & Hospitality, eCommerce, and other industries.

Project :

The project focuses on building a modern, cloud-native data platform that enables reliable, scalable, and secure data processing across structured, semi-structured, and unstructured data sources.

The role involves developing high-quality data pipelines, data products, and integrations using AWS and Snowflake, while supporting enterprise-wide analytics, AI, and business intelligence initiatives.

The project emphasizes software engineering best practices, automation, CI/CD, observability, and AI-assisted development to deliver maintainable, production-grade solutions with a strong focus on performance, governance, and operational excellence.

Responsibilities :

• Design, build, and operate production-grade software and data solutions end-to-end, from problem definition and architecture through implementation, deployment, monitoring, and continuous improvement.

• Design and implement reliable, scalable, secure, and well-governed data pipelines and data products using AWS and Snowflake across structured, semi-structured, and unstructured data sources.

• Model, curate, and optimize Snowflake datasets, schemas, and data structures in line with enterprise platform standards, ensuring performance, quality, consistency, and usability for downstream consumers.

• Apply strong software engineering practices, including clean code, modular design, automated testing, CI/CD, observability, secure development, and maintainable architecture.

• Collaborate with business and technical stakeholders to translate requirements into robust data solutions, prioritize delivery, and identify opportunities to enable advanced analytics and AI use cases.

• Use AI-assisted engineering as a standard part of daily development to accelerate coding, refactoring, documentation, testing, debugging, and solution exploration while maintaining strong engineering judgment and quality standards.

• Build cloud-native integrations and automation on AWS, effectively using services related to compute, storage, networking, security, orchestration, event-driven architectures, and managed AI services where appropriate.