diff --git a/src/pudl_archiver/archivers/nrelcambium.py b/src/pudl_archiver/archivers/nrelcambium.py
new file mode 100644
index 00000000..84e27c5f
--- /dev/null
+++ b/src/pudl_archiver/archivers/nrelcambium.py
@@ -0,0 +1,152 @@
+"""Download NREL Cambium Scenarios data."""
+
+import io
+import re
+from contextlib import nullcontext
+from pathlib import Path
+
+import aiohttp
+
+from pudl_archiver.archivers.classes import (
+    AbstractDatasetArchiver,
+    ArchiveAwaitable,
+    ResourceInfo,
+)
+from pudl_archiver.utils import retry_async
+
+
+async def _download_file_post(
+    session: aiohttp.ClientSession, url: str, file: Path | io.BytesIO, **kwargs
+):
+    async with session.post(url, **kwargs) as response:
+        with file.open("wb") if isinstance(file, Path) else nullcontext(file) as f:
+            async for chunk in response.content.iter_chunked(1024):
+                f.write(chunk)
+
+
+class NrelCambiumArchiver(AbstractDatasetArchiver):
+    """NREL Cambium archiver."""
+
+    name = "nrelcambium"
+
+    async def get_resources(self) -> ArchiveAwaitable:
+        """Download NREL Cambium resources."""
+
+        async def post_to_json(url, **kwargs):
+            resp = await retry_async(self.session.post, [url], kwargs={"data": kwargs})
+            return await retry_async(resp.json)
+
+        project_year_pattern = re.compile(r"Cambium (?P<year>\d{4})")
+        report_url_pattern = re.compile(
+            r"https://www.nrel.gov/docs/(?P<fy>fy\d{2}osti)/(?P<number>\d{5}\.pdf)"
+        )
+
+        project_records = await self.get_json(
+            "https://scenarioviewer.nrel.gov/api/projects/"
+        )
+        for scenario_project in (
+            p for p in project_records if p["name"].startswith("Cambium")
+        ):
+            project_uuid = scenario_project["uuid"]
+            m = project_year_pattern.search(scenario_project["name"])
+            if not m:
+                continue
+            project_year = int(m.group("year"))
+
+            report_link_section = "long_description"
+            report_links = self.get_hyperlinks_from_text(
+                scenario_project[report_link_section], report_url_pattern
+            )
+            if not report_links:
+                raise AssertionError(
+                    f"We expect all years to have a {report_link_section} with a link to the report, but {project_year} does not:"
+                    f"{scenario_project}"
+                )
+            report_data = []
+            for report_link in report_links:
+                m = report_url_pattern.search(report_link)
+                if not m:
+                    raise AssertionError(
+                        f"Bad link {report_link} found in {project_uuid}: {scenario_project}"
+                    )
+                report_data.append(
+                    (f"{m.group('fy')}_{m.group('number')}", report_link)
+                )
+
+            file_list = await post_to_json(
+                "https://scenarioviewer.nrel.gov/api/file-list/",
+                project_uuid=project_uuid,
+            )
+            yield self.get_year_resource(
+                reports=report_data,
+                uuid=project_uuid,
+                file_ids=[
+                    (
+                        f["id"],
+                        f"NRELCAMBIUM {project_year}  {f['scenario']}  {f['metric']}  {f['time_resolution']}  {f['location_type']}.{f['file_type']}".replace(
+                            " ", "_"
+                        )
+                        .replace("%", "pct")
+                        .replace(",", "")
+                        .lower(),
+                    )
+                    for f in file_list["files"]
+                    if (f["file_type"] == "CSV" or project_year == 2020)
+                ],
+                year=project_year,
+            )
+
+    async def get_year_resource(
+        self, reports, uuid, file_ids, year: int
+    ) -> ResourceInfo:
+        """Download all available data for a year.
+
+        Resulting resource contains one pdf of the scenario report, and a set of CSVs for different scenarios and geo levels.
+
+        Args:
+            links: filename->URL mapping for files to download
+            year: the year we're downloading data for
+        """
+        zip_path = self.download_directory / f"{self.name}-{year}.zip"
+        data_paths_in_archive = set()
+        # reports
+        for report in reports:
+            self.logger.info(f"Downloading report {year} {report[0]} from {report[1]}")
+            download_path = self.download_directory / report[0]
+            await self.download_file(report[1], download_path)
+            self.add_to_archive(
+                zip_path=zip_path,
+                filename=report[0],
+                blob=download_path.open("rb"),
+            )
+            data_paths_in_archive.add(report[0])
+            # Don't want to leave multiple giant files on disk, so delete
+            # immediately after they're safely stored in the ZIP
+            download_path.unlink()
+
+        for file_id, filename in file_ids:
+            self.logger.info(f"Downloading file {year} {file_id} {uuid}")
+            download_path = self.download_directory / filename
+            await retry_async(
+                _download_file_post,
+                [
+                    self.session,
+                    "https://scenarioviewer.nrel.gov/api/download/",
+                    download_path,
+                ],
+                kwargs={"data": {"project_uuid": uuid, "file_ids": file_id}},
+            )
+            self.add_to_archive(
+                zip_path=zip_path,
+                filename=filename,
+                blob=download_path.open("rb"),
+            )
+            data_paths_in_archive.add(filename)
+            # Don't want to leave multiple giant files on disk, so delete
+            # immediately after they're safely stored in the ZIP
+            download_path.unlink()
+        return ResourceInfo(
+            local_path=zip_path,
+            partitions={"years": year},
+            # layout=ZipLayout(file_paths=data_paths_in_archive), # can't use ZipLayout bc these CSVs have a multi-row header and pandas throws a tantrum
+        )