Data Engineer

Role Overview

Data Engineering

• Write Python scripts to acquire data and process data from various academic, government, or commercial sources for use in Meridia’s product development
• Maintain accurate, high-quality metadata on the company’s internal datasets using scripts, automation, and selected tooling
• Develop internal tools and scripts to automate data processing and use technologies like Airflow, AWS, Google Cloud to scale and optimise ETL tasks of geospatial data
• Maintain the team’s git repository of ETL scripts and adhere to version control best practices to ensure code is well organized, accessible, and reproducible by the entire team
• Optimize data ingestion processes to ensure reliable, timely, and scalable delivery of data into downstream products and analytics workflows, particularly for large-scale raster and vector datasets
• Monitor ingestion pipelines with logging, alerting, and metrics to detect failures or data inconsistencies
• Contribute to our (internal) data catalogues, manuals, dictionaries, glossary and broader set of terminology in a coherent way across countries, products and projects.
• Drive continuous improvements in operational efficiency by identifying bottlenecks and implementing solutions

Core Data Engineering Skills

• Expertise in building, optimizing, and maintaining scalable ETL/data pipelines, especially for large and complex geospatial datasets, using modern orchestration and workflow tools such as Apache Airflow.
• Proficient in cloud platforms (e.g. AWS), with hands-on experience architecting data storage, transformation, and metadata solutions in a secure and cost-effective manner using Infrastructure as Code tools such as Terraform
• Skilled in Python and relevant data engineering frameworks (e.g., Pandas, Pydantic, Rasterio, Tippecano) for automating data ingestion, cleaning, standardisation, and geospatial transformation.
• Solid understanding of data governance and best practices in version control (e.g., Git), documentation, data quality assurance, reproducibility, and collaboration in cross-functional data teams.

Learning and DevelopmentThe ideal candidate should be eager and willing to learn and grow in the role. You will be engaged in on-the-job training and development to learn about the land rights sector and our data systems and workflows. You will be mentored by our Data Engineering team in Indonesia and senior colleagues in the Netherlands.

Requirements

The ideal candidate has/is

• 4+ years of experience in a relevant role
• Rigorous problem-solving and analytical skills
• Ability to effectively and efficiently collect and organise data from multiple sources
• Understanding of data management and data entry processes
• Independently driven, proactive, accountable, and a reliable team player
• Full working proficiency in English

The following are an advantage:

• Familiarity with GIS scripting (python, geopandas, PostGIS) and GIS software like QGIS ETL experience.
• Demonstrated projects or case studies involving forest monitoring or land-use analysis
• Experience with data version control tools such as DVC
• Start-up experience.

Tech Stack

• Airflow
• Apache
• AWS
• Cloud
• ETL
• Pandas
• PostGIS
• Python
• Terraform

Benefits

The benefits package includes

• Market rate salary commensurate with your skills and competencies
• Four-day work week
• A remote working position
• Being part of a fast-growing impact venture with an informal, professional work culture
• A laptop and an external monitor for your work
• Annual employee led Learning & Development budget
• Being part of a fast-growing impact venture with an informal, professional work culture
• Engaging with team members, clients and users in various other countries