Unlocking the full potential of forests, both ecologically and emotionally.
Job Overview
We’re looking for a skilled Data Engineer to design, build, and maintain robust data pipelines and infrastructure focused on geospatial and temporal datasets. You’ll play a key role in processing complex environmental data, enabling real-time analytics, and supporting our mission to create a greener planet. If you’re passionate about data systems, geospatial technology, and sustainability, we’d love to hear from you!
Key Responsibilities
- Data Pipeline Development: Design and implement scalable ETL/ELT pipelines to ingest, process, and transform geospatial and temporal data from diverse sources (e.g., satellite imagery, IoT sensors, historical records).
- Geospatial Data Management: Optimize storage and querying of geospatial datasets using tools like PostGIS, GeoPandas, or similar technologies.
- Temporal Data Processing: Build systems to handle time-series data, ensuring efficient analysis of trends and patterns over time.
- Infrastructure Optimization: Develop and maintain data architectures (e.g., data lakes, warehouses) on cloud platforms to support high-volume geospatial and temporal workloads.
- Collaboration: Partner with data scientists and product teams to deliver clean, reliable datasets for visualization, machine learning, and decision-making.
- Performance Tuning: Monitor and enhance the performance of data systems, ensuring low-latency access to geospatial and temporal insights.
- Data Quality & Security: Implement processes to ensure data accuracy, consistency, and compliance with privacy standards.
Required Skills & Qualifications
- Experience: 3+ years in data engineering or a related role, with hands-on experience in geospatial and/or temporal data processing.
- Programming: Proficiency in Python, SQL, and familiarity with languages like Java or Scala.
- Geospatial Tools: Experience with geospatial libraries (e.g., GDAL, GeoPandas, QGIS) and databases (e.g., PostGIS).
- Data Technologies: Knowledge of big data frameworks (e.g., Apache Spark, Kafka) and time-series databases (e.g., InfluxDB, TimescaleDB).
- Cloud Expertise: Practical experience with cloud platforms (AWS or Azure) and their geospatial/temporal data services (e.g., BigQuery GIS, S3).
- Problem-Solving: Strong analytical skills to tackle complex data challenges.
- Education: Bachelor’s degree in Computer Science, Engineering, GIS, or a related field (or equivalent experience).
Nice-to-Haves
- Experience with environmental or sustainability-focused datasets.
- Familiarity with real-time data streaming and processing.
- Contributions to open-source geospatial or data engineering projects.
About us
At Tree.ly, we are fully committed to climate protection and enhance the importance of forests as critical ecosystems through innovative business models. We connect companies and forest owners to sustainably and climate-resiliently manage forests through direct investments. Our vision is to create a future where forests are valued for their ecological services and managed sustainably in alignment with business interests.
