About the Role

We are a young startup, looking for a passionate candidate who can contribute to our mission to deploy impactful solutions to the most important issue of our generation. Our focus is on developing climate adaptation & resilience tools for multiple sectors, with agriculture as our initial market. We are looking for a Data Engineer familiar with designing robust and scalable data processes from the ground up. Experience with infrastructure is a bonus.

This person will help found a new Data Engineering group at ClimateAi and create the next model for our climate and weather data flows. We work with a range of data types from hyper-structured n-dimensional data at terabyte scale to heterogeneous sensor data, with the need to deliver high quality information to data scientists (ML research) and operational products. This individual should be able to work remotely and be supremely self-driven with a strong sense of teamwork and collaboration. The ideal candidate will have a deep passion for designing and building data systems from the ground up, and an unwavering commitment to quality.

Also, the candidate will be working on shaping the vision of the company and brand Climate Tech. The ideal candidate will be comfortable working on open-ended projects, both individually as well as in a fast-paced team environment. We hire people who are collaborative, adaptable, communicate well, and love to learn. Expect to give and receive constructive criticism, as we are constantly re-evaluating our hypotheses and our products.

Main Responsibilities:

• Develop and own creative solutions to diverse challenges that span data processing, data modeling, and machine learning model deployment. We are looking for builders who love working from the ground up in a team environment.
• Create flexible solutions that adapt to data quality and availability, and allow rapid correction on new edge cases.
• Collaborate with product, backend, and data science teams to identify needs, evaluate requirements, write specifications, and design and implement data flows and data storage.
• Partner with backend and data science team members to understand and optimize downstream data usage.
• Have a direct impact on the technical direction and product roadmap of the company.
• Create documentation and tech plans for new architecture/system designs
• Write well crafted, efficient and testable code in Python / Java 
• Conduct regular code reviews to ensure high quality
• Grow with the business; stretch yourself and learn new skills and domains.
• Mentor others on the team to help them succeed.

Desired Skill and Experience:

• 2+ years proven experience in data engineering
• 2+ years of experience in the custom ETL design, implementation, and maintenance
• Experience with data architecture, data modeling, schema design, and software development
• 2+ years of experience in SQL / NoSQL, and development experience in at least one language (Python, Java etc.)
• Experience with Cloud Infrastructure like GCP, AWS, or Azure
• Ability to translate business requirements into technical solutions.
• Comfortable understanding and debugging unfamiliar code in a large project.
• Proven track record collaborating with other partners to design and implement features and systems with excellent problem solving skills.
• Good communication skills – particularly the ability to discuss timelines, design concerns and provide helpful feedback to team members

The following skills are considered strong pluses but are not required:

• Experience with frameworks for:
  • Distributed processing: Dask, Spark, or similar
  • Storage: Zarr, TileDB, PostgreSQL, or Redis (or other NoSQL)
• Experience with spatial and time series data, especially weather and geospatial datasets
• Data infrastructure experience: Kubernetes, Terraform, Airflow, resource optimization
• Visualizing data flows and data quality