Senior Data Engineer​

 

About Natural State  

Natural State is an international NGO based in northern Kenya, dedicated to laying the groundwork for a resilient restoration economy. We design and develop the technologies and scientific methods required to support credible, nature-based financial mechanisms. By reducing technical barriers and improving access to high-quality ecological information, we are building monitoring tools and systems that offer cost-effective, reliable measurement of biodiversity, carbon, water, and social indicators.  
  

The Research & Monitoring (R&M) Department leads all scientific data collection, ecological monitoring, verification, and analysis across landscapes. As Natural State deepens its R&D work, we are expanding our scientific capabilities to design and refine monitoring tools that support restoration and conservation across diverse ecosystems.  

 

Location: Remote with 5 working hours of overlap with EAT 

Department: Head of Conservation technology 

Terms: Full time (40 hrs per week) 

Travel: Occasional travel to Africa (1-3 times a year)   
 

Role Overview 

We are seeking a Senior Data Engineer to build and maintain the data systems that power Natural State’s impact monitoring work. You will be responsible for developing scalable cloud infrastructures, data ingestion and modelling pipelines, and ML-enabled applications that translate ecological field data into actionable insights. This role is central to bridging scientific workflows with production-grade engineering and will collaborate closely with R&D teams and external partners. 

You will build the data backbone that powers global restoration monitoring—turning raw ecological data into trusted, scalable insights for conservation partners worldwide. 

 

Key Responsibilities 

• Design, develop, and maintain scalable data pipelines and architectures using Azure cloud services, with eventual expansion into AWS and Google Cloud Platform (GCP). 

• Manage and optimize big data environments to ensure efficient data processing and storage. 

• Utilize Databricks for advanced data analytics, including Databricks Autoloader for seamless data ingestion and Databricks Unity Catalog for data governance. 

• Implement and manage data models and schema using Data Build Tool (DBT) to ensure robust and scalable data structures. 

• Apply Great Expectations for data quality checking (QA/QC) to maintain high standards of data integrity and reliability. 

• Develop and maintain CI/CD pipelines using GitHub Actions to automate deployment and ensure continuous integration. 

• Deploy and manage Kubernetes clusters using Helm for container orchestration and application deployment. 

• Utilize Apache Spark for distributed data processing and analytics to handle large-scale datasets. 

• Assist in the deployment of web applications to provide user-friendly interfaces for data access and analysis. 

• Leverage Azure Machine Learning to train and deploy machine learning models tailored to nature conservation and restoration. 

• Implement automated infrastructure deployment using Terraform and Terragrunt to ensure efficient, reproducible environments. 

 

Required Qualifications & Experience 

• Bachelor's or master's degree in computer science, Data Engineering, or a related field. 

• 5+ years of hands-on data engineering experience, with at least 3 years in a senior or architect role designing and deploying scalable data platforms. 

• Core Cloud and Data Platform Expertise: 

• Proven production experience with Azure (mandatory). 

• Experience with AWS and/or GCP is highly preferred. 

• Strong proficiency in Databricks, including Autoloader and Unity Catalog. 

• Advanced skills in Apache Spark for distributed data processing. 

• Data Engineering Tooling: 

• Extensive experience with Data Build Tool (DBT) for data modelling and transformation. 

• Hands-on experience with Great Expectations for data quality and validation. 

• Experience with Terraform/Terragrunt for Infrastructure as Code (IaC). 

• DevOps and Orchestration: 

• Proficiency in Kubernetes and Helm for container orchestration. 

• Experience building CI/CD pipelines using GitHub Actions or similar. 

• ML Engineering Exposure: 

• Practical experience with Azure Machine Learning or similar ML platforms for model training and deployment. 

• Soft Skills and Environment: 

• Excellent problem-solving skills and ability to communicate complex technical concepts to non-technical stakeholders. 

• Ability to work independently in a fully remote, globally distributed team. 

• Mission-driven mindset with interest or experience in conservation, environmental science, or NGO/scientific collaboration. 

 

Preferred Qualifications 

• Experience with geospatial data processing (e.g., raster/vector data, satellite imagery). 

• Familiarity with environmental/climate data standards or scientific data workflows. 

• Prior work in startup, NGO, or research-intensive environments. 

• Contributions to open-source data or conservation tech projects. 

 

What We Offer 

• A competitive salary commensurate with experience and qualifications. 

• 22 days of annual leave, additional office closure days in December, all public holidays, a pension scheme, and comprehensive medical cover. 

• Opportunity to shape and lead a new division at the forefront of conservation monitoring. 

• Close collaboration with mission-driven scientists, technical specialists, and conservationists, both internally and through partnerships with world-class academic institutions. 

• A dynamic, supportive, and fully remote work environment committed to scientific integrity and ecological restoration. 

• The chance to build and grow the data engineering function from the ground up in a high-impact, purpose-driven organization. 

 

How to Apply 

Please submit using the Apply button below. Applications will be reviewed on a rolling basis. Natural State is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.