Data Engineer

ABOUT US 

EarthDaily Agro provides space age data and analytics to the organizations and people who feed the planet!   

With 35 years of industry experience, EarthDaily Agro provides customers with the data, analysis and knowledge they need to make more efficient and effective decisions. B2B services range from global risk management and monitoring of agricultural commodities to the marketing of inputs and precision agriculture consulting, using the latest research in agronomy, information technologies and remote sensing.    

EarthDaily Agro also develops highly customized business solutions for agricultural lenders, insurers, input suppliers and food companies, with easy-to-use analytics, that help reduce the daily risks of agriculture.    

EarthDaily Agro is headquartered in Minneapolis, MN, USA, with offices in France, Brazil, Australia and Switzerland and is a division of EarthDaily Analytics Corp.     

EarthDaily Analytics Corp., a vertically-integrated data processing and analytics company, is launching a new constellation of earth observation satellites. The EarthDaily satellite constellation will significantly enhance geospatial analytics capabilities in agriculture, forestry, environment, financial services, and intelligence, among many other verticals.   

MAIN JOB TASKS AND RESPONSIBILITIES

As a EarthDailyAgro Data Engineer, your primary responsibility will be to design, develop, and manage data pipelines and infrastructure specialized for geospatial and remote sensing applications. You will work closely with data scientists, geospatial analysts, remote sensing experts, software engineers, and DevOps teams to ensure the successful deployment and scaling of data pipeline to feed geospatial data machine learning models. Your role will be crucial in optimizing the geospatial machine learning ecosystem and ensuring the seamless integration of AI-driven geospatial solutions into real-world applications.  

YOUR RESPONSIBILITIES INCLUDE

• Cloud-based data pipeline Conceptualization, Development and Scaling: Build up pipeline to ingest large volumes of geospatial data, pre-process them and meet data scientists’ requirements, in terms of accessibility, speed, format, quality. 

• Automation and CI/CD: Industrialization of pipeline deployment, orchestration, workflows, and versioning.  

• Cost & Speed Optimization: Collaborate with infrastructure team to develop, optimize, and fine-tune pipeline.  

• Cloud and Containerization: Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization tools.   

• Infrastructure Management: Utilize containerization technologies and cloud-based services to set up and manage infrastructure, enabling seamless deployment and scalability.  

• Monitoring and Anomaly Detection: Implement monitoring systems to track pipeline performance and identify anomalies.  

• Version Control and Data Version Control: Proficient with version control systems like Git and DVC.  

• Security and Compliance: Ensure the security and privacy of geospatial data, adhering to relevant data protection regulations and industry best practices.  

• Collaboration and Communication: Collaborate with interdisciplinary teams to integrate data pipeline into existing applications or develop new geospatial products.  

• Issue Resolution and Troubleshooting: Identify and resolve promptly technical issues related to geospatial data processing, performance, or infrastructure.  

EDUCATION, KNOWLEDGE AND ABILITIES 

Requirements  

• Education: Master's degree in Computer Science, specialisation in Geomatics and/or Remote sensing would be a plus.  

• Experience: 3+ years experiences with data pipeline processes and deployment is a must-have. Proven hands-on experience in setting up pipelines and data processes with opensource tools (e.g., MLFlow, Argo, Kubeflow) is desirable.  

• Programming Skills: Proficiency in Python and with data manipulation frameworks (e.g., dataframe, numpy, pandas, xarray, rasterio) and librairies (e.g., Dask).  

• Problem-Solving Skills: Autonomous, and strong analytical and problem-solving abilities to address complex geospatial data and analysis challenges.  

• Communication Skills: Excellent communication and interpersonal skills to collaborate effectively with cross-functional teams and stakeholders.  

• French mandatory (job based in France). Fluent in English (oral and written): meetings with internal are mostly in English.   

Preferred Additional Skills 

• Experience with Earth Observation (EO) data analysis and processing.  

• Experience with geospatial data formats (e.g., GeoTIFF, Shapefile, NetCDF). 

• Spatial Analysis Techniques: Understanding of spatial analysis techniques and algorithms commonly used in geospatial data manipulation.  

• Remote Sensing Integration: Knowledge of remote sensing data sources (e.g., STAC catalog, satellite imagery, LiDAR, SAR) integration into data pipelines for accurate and up-to-date geospatial analysis.  

CONDITIONS  

Full time job based in Balma, near Toulouse, France.  

Fixed + Bonuses  

TR / "Family" insurance / CSE