Data Engineer (AWS)

Location : Bengaluru, Karnataka

About the Company :

Sustainability Economics.ai is a global organization, pioneering the convergence of clean energy and AI, enabling profitable energy transitions while powering end-to-end AI infrastructure. By integrating AI-driven cloud solutions with sustainable energy, we create scalable, intelligent ecosystems that drive efficiency, innovation, and long-term impact across industries. Guided by exceptional leaders and visionaries with decades of expertise in finance, policy, technology, and innovation, we are committed to making long-term efforts to fulfil this vision through our technical innovation, client services, expertise, and capability expansion.

Role Summary :

We are seeking a skilled and experienced Data Engineer with a minimum of 2 years of experience in AI-driven data pipelines, agentic databases, and orchestration frameworks. The role focuses on designing intelligent, scalable, and adaptive data architectures that support next-generation AI-based systems and applications. The ideal candidate will have a strong background in AWS services (including Glue, EMR, and Lambda), along with expertise in data modelling, Python, SQL , and hands-on experience in integrating third-party APIs from the ground up.

Key Responsibilities :

• Design, develop, and maintain AI-driven, agentic data pipelines and intelligent end-to-end architectures that support scalable, adaptive systems.
• Build and optimize data models and schemas that adapt to evolving business needs, ensuring flexibility across structured and unstructured data.
• Integrate AI-driven components and advanced data workflows into production systems for seamless orchestration and automation.
• Work with cross-functional teams and stakeholders to turn business requirements into technical solutions.
• Implement scalable pipelines on AWS using services such as S3, Glue, EMR, Lambda, and DynamoDB for reliability and performance.
• Develop and manage ETL / ELT pipelines, integrating third-party APIs and diverse data sources with accuracy and consistency.
• Apply best practices in data governance, lineage, and observability with modern monitoring tools.
• Optimize SQL queries, storage, and throughput to improve efficiency across data systems.
• Document pipelines, data flows, and transformations to ensure clarity and maintainability.
• Explore emerging tools in agentic systems, orchestration frameworks, and AWS to continuously strengthen the data engineering ecosystem.

Key Requirements

Education and Experience :

What You’ll Do :

What You Bring :

Why Join Us