Data Engineer

December 6

Apply Now

Receive Emails with Similar Jobs

Nacre Capital

WebsiteLinkedInAll Job Openings

Artificial Intelligence • Start-Ups • Deep Learning • Technology • Innovation

11 - 50 employees

🤝 B2B

💳 Fintech

🧬 Biotechnology

Description

• About Us: • Aquaticode builds artificial intelligence solutions for aquaculture. • Our core competency lies at the intersection of biology and artificial intelligence, utilizing specialized imaging technology to detect, identify, and predict traits of aquatic species. • We value commitment and creativity in building real-world solutions that benefit humanity. • Key Responsibilities: • Develop, maintain, and optimize data pipelines and workflows to support ML research and model development. • Design and implement scalable data architectures for handling large datasets used in ML models. • Collaborate closely with ML researchers and data scientists to understand data requirements and ensure data availability and quality. • Work with databases and data integration processes to prepare and transform data for ML experiments. • Utilize MongoDB and other NoSQL databases to manage unstructured and semi-structured data. • Write efficient, reliable, and maintainable code in Python and SQL for data processing tasks. • Implement data validation and monitoring systems to ensure data integrity and performance. • Support the deployment of ML models by integrating data solutions into production environments. • Ensure the scalability and performance of data systems through rigorous testing and optimization.

Requirements

• Proficiency in English (spoken and written). • Strong experience in Python and SQL. • Hands-on experience with data processing in Apache Airflow. • Experience working with databases, including MongoDB (NoSQL) and relational databases. • Understanding of data modeling, ETL processes, and data warehousing concepts. • Experience with cloud platforms like AWS, GCP, or Azure. • Experience with other NoSQL databases like InfluxDB, Elasticsearch, or similar technologies. • Experience with backend frameworks like FastAPI, Flask, or Django. • Knowledge of containerization tools like Docker. • Familiarity with messaging queues like RabbitMQ. • Understanding of DevOps practices and experience with CI/CD pipelines. • Experience with front-end development (e.g., React, NextJs).