Optimization and ML Modelling Engineer

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.    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.    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.  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.    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.  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.    Passion for AI, agentic architectures, and next-gen data systems .  Ability to collaborate across engineering, product, and data science teams.  Agile mindset, adaptability, and eagerness to learn emerging technologies.    Shape a first-of-its-kind AI + clean energy platform .  A chance to leave your mark at the intersection of AI, design, and sustainability .