Job Boards
By country
France United Kingdom Germany United States Switzerland Netherlands Spain Italy Belgium Canada Sweden Singapore
All countries
Companies Blog Support us
Browse all roles

Geospatial Data Engineer, WW Sustainability

Amazon • United States • Added on Oct 30, 2026
Apply →

This engineer will build and maintain the data systems that turn geospatial information into usable inputs for Amazon’s sustainability assessments. The work spans climate, weather and socioeconomic datasets, from data quality and processing through to metrics, reporting and services used by internal teams. The focus is on reliable infrastructure that can support analysis at global scale.

The data helps the Worldwide Sustainability team assess environmental impacts and inform operational planning. By preparing spatial risk factors, such as hazards and vulnerability, the role connects climate and social data to decisions across a large business. Its contribution is enabling the measurement and analysis behind environmental performance and future abatement planning, rather than setting sustainability policy.

This suits someone with several years of data engineering experience and a strong grasp of raster and vector geospatial formats, GIS tools and distributed pipelines. A candidate who can work across scientists, engineers and program teams, while making complex data dependable and usable, is likely to find the role a good fit.

Job FAQs

What are the main missions and responsibilities of this role?

The core mission is to operate geospatial datasets and build the pipelines that turn climate, weather and socioeconomic sources into dependable risk factors. This includes ingestion, documentation, data quality, metadata, storage and access through data services or APIs. The engineer also supports sustainability measurement with metrics, reporting tables and dashboards, working with science and engineering colleagues to make analytical models usable at scale. The broader aim is to provide credible data for environmental impact assessments and business planning.

Key learning opportunities for this job

The role could deepen expertise in geospatial data engineering, including raster and vector formats, GIS tooling and processing large spatial datasets. Work across AWS services and frameworks such as Spark, Glue and Airflow may also broaden cloud architecture and production pipeline skills. Close collaboration with scientists could provide exposure to climate and socioeconomic risk analysis, while reporting and governance work offers experience translating technical data into decision support.

How does the ideal candidate look like (experience, skills)?

A strong candidate would bring at least three years of data engineering experience, including data modeling, warehousing, ETL pipelines and delivery of end-to-end projects. The posting specifically calls for deep familiarity with raster and vector geospatial data and GIS tools. Experience with distributed data systems, Python, Java or Scala, and AWS services such as S3, Redshift, Glue or EMR would be relevant. The work also calls for careful data stewardship and the ability to collaborate with scientific, engineering and program teams.

Advice to stand out and make a successful application

Make the application concrete: describe a geospatial or other large-scale data project from source ingestion through validation, modeling and production use. Name the data formats, GIS tools, cloud services and processing frameworks you used, and explain how you handled quality, metadata and reliability. For interviews, prepare an example of how your pipeline or dataset supported a decision. Connect the technical outcome to environmental measurement or risk analysis where your experience allows, without claiming sustainability expertise you have not built.

What aspects of the company's sustainability is this role likely to focus on?

The role supports Amazon's Worldwide Sustainability measurement and abatement technology work. Its likely focus is preparing climate, weather and socioeconomic geospatial data for environmental impact assessments and area-based risk analysis. This infrastructure can inform operational planning and sustainability metrics, including areas such as carbon, water and waste identified in the posting. The engineer enables measurement and analysis, while the source does not assign direct ownership of emissions reductions or sustainability targets.

What are the main challenges someone in this role might face?

A likely challenge is consolidating inconsistent data from multiple internal and external sources while preserving quality, provenance and usable metadata. Raster and vector datasets may differ in format, scale and coverage, so pipelines need to handle those differences reliably. The role must also balance scientific needs with production standards, governance, security and changing reporting requirements. Making data suitable for both complex analysis and operational decisions could require careful coordination across teams.

How could a typical day look like for someone in this position?

A day could include reviewing data pipeline health, resolving quality or ingestion issues, and developing transformations for geospatial datasets. The engineer might also work on AWS infrastructure, test deployments, update metadata or improve a reporting table or dashboard. Time would likely be shared with scientists, engineers and program or product colleagues to clarify data needs and move analytical work into production. Priorities may vary as new sources, risk assessments or reporting needs arise.

What are the opportunities for professional growth and development in this role?

The role could build a path toward senior data engineering or platform leadership through ownership of production geospatial systems and broader architecture work. Further growth may come from deepening expertise in cloud data platforms, GIS and large-scale spatial analytics. Working alongside scientists may also develop knowledge of climate risk and environmental measurement. The posting describes collaboration and a reporting roadmap, but does not specify a promotion path or formal training program.

The main stakeholders you might be interacting with

Key partners would likely include sustainability measurement and abatement technology colleagues, especially scientists who develop analytical methods. Data and software engineers would work with the role on pipeline architecture, integrations and operational reliability. Product and program teams are also relevant partners, since they identify business questions and use reporting or risk data in planning. Internal users of sustainability metrics may rely on the resulting datasets, dashboards and APIs.

CSR Jobs newsletter

Never miss the next opportunity

Get a curated selection of new CSR, ESG, and sustainability roles in your inbox. No daily noise, just useful opportunities.

Free to join. Unsubscribe anytime.