Raad Labs - Founding Data Engineer - Job Description

Pioneering the human-nature interface, Raad is laying the digital sensory nervous system for our planet. Our distributed sensor network doesn't just collect meteorological data—it extends society’s perception, enabling institutions to navigate a changing climate in ways previously unimaginable.

As a founding data engineer at Raad, you'll be at the helm of this revolution, architecting DePIN systems that transform previously inaccessible raw weather inputs into actionable intelligence for people, governments, and businesses. Join us in bolstering better ground-truth about what goes on around us, empowering humanity to make better decisions and fostering harmony between our species and the world we inhabit.

We're seeking an exceptional data engineer to sculpt and lead our advanced data infrastructure initiatives. The ideal candidate will possess a unique blend of technical expertise, analytical skills, and a deep understanding of complex data systems and algorithms.

Key Responsibilities:

• Architect scalable, high-performance data pipelines and storage solutions for petabyte-scale datasets
• Implement and optimize advanced ETL/ELT processes
• Develop and maintain data models supporting advanced analytics and machine learning
• Ensure data quality, security, and compliance across all systems
• Collaborate with cross-functional teams to align technical solutions with business needs
• Lead initiatives to improve data accessibility, reliability, and efficiency

Required Skills and Qualifications:

• Expert-level programming in Python, SQL, and Scala
• Mastery of big data technologies (e.g., Apache Spark, Flink)
• Extensive experience with cloud platforms (AWS, Azure, GCP) and their data services
• Strong background in distributed systems and parallel computing
• Proficiency in data visualization and real-time analytics
• Solid grasp of statistics, machine learning, and statistical inference
• Experience with graph databases, network analysis, and high-dimensional data handling

Preferred Qualifications:

• Knowledge of spatial databases and GIS technologies
• Proficiency in topological methods and Information Theory
• Experience with signal processing, Fourier analysis, and time series analysis
• Understanding of optimization algorithms and Bayesian methods
• Knowledge of data governance and compliance standards
• Familiarity with DevOps practices and CI/CD pipelines

Key Competencies:

• Ability to design and optimize complex data architectures for maximum efficiency and scalability
• Strong problem-solving skills with a focus on innovative solutions for big data challenges
• Excellent communication skills to explain advanced technical concepts to diverse stakeholders
• Proactive approach to identifying and addressing data-related challenges
• Continuous learning mindset to stay updated with cutting-edge data engineering trends and technologies

The ideal candidate will demonstrate not just technical proficiency, but also a deep understanding of advanced mathematical concepts and their application in data engineering. They should be able to leverage techniques from ac