Data Engineer

3 days ago


Yelahanka, India Sustainability Economics.ai Full time

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: - Bachelor’s degree in Computer Science, Data Engineering, or a related field. - Minimum of 2 years of experience in data engineering, with exposure to AI-driven or agentic systems. - Strong proficiency in AWS services including S3, Glue, EMR, Lambda, DynamoDB, and Postgres, along with familiarity with AI-focused databases. - Hands-on experience in data scraping, data modeling, schema design, and relational database concepts. - Solid working knowledge of SQL, including performance tuning and query optimization best practices. - Prior experience in integrating APIs and AI components into data pipelines. What You’ll Do: - Build adaptive data pipelines that can self-optimize and scale with business needs. - Develop and manage systems that support multimodal data (text, geospatial). - Enable real-time transformations in pipelines using agentic architectures. - Contribute to the evolution of agentic databases and autonomous data workflows. What You Bring: - Passion for AI, agentic architectures, and next-gen data systems. - Strong problem-solving ability and a drive for innovation. - Ability to collaborate across engineering, product, and data science teams. - Agile mindset, adaptability, and eagerness to learn emerging technologies. Why Join Us - Shape a first-of-its-kind AI + clean energy platform. - Work with a small, mission-driven team obsessed with impact. - An aggressive growth path. - A chance to leave your mark at the intersection of AI, design, and sustainability.


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