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

Meridia

Open Positions (1)

Engineering

Data Engineer