Our new product is an AI-powered market intelligence and analytics platform helping commodity professionals make faster, smarter, and more informed decisions.
We’re looking for a Data Engineer to join our team and work at the intersection of Data Engineering, Backend Development, and Applied AI.

What You’ll Do
Build and maintain ETL, data extraction, and processing pipelines
Develop backend services and APIs using Python & FastAPI
Build asynchronous and scheduled workflows with Celery
Work with PostgreSQL and MongoDB
Ensure data quality, including missing, stale, duplicate, and invalid data
Debug and monitor production pipelines and background jobs
Integrate existing ML models and LLM-based services into production workflows
Contribute to AI-powered analytical features
Write clean, testable, and maintainable Python code
Participate in code reviews and technical discussions

What We’re Looking For
Must Have
2+ years of relevant experience
Strong Python skills
Hands-on experience with FastAPI
Strong SQL & PostgreSQL knowledge
Practical experience with ETL/data pipelines
Experience with Celery, including retries and failure handling
Experience with Git, Docker, testing, and production debugging

It Would Be Good to Have
MongoDB
Redis and/or RabbitMQ
Basic–intermediate understanding of Machine Learning
Experience integrating LLM/Generative AI services
scikit-learn, fuzzy logic, embeddings, or vector databases
Experience with financial, commodity, or time-series data

What We Value
We’re looking for someone who is strong in data engineering and backend development, curious about AI, comfortable solving real-world data problems, and excited to build reliable systems in a fast-moving product environment.