diff --git a/CHANGELOG.md b/CHANGELOG.md
index cbc0c92..3e3cdbe 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -8,6 +8,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 ## [Unreleased]
 
 ### Changed
+- **Breaking:** the pipeline config is validated against an explicit pydantic schema (`mxalign.pipeline.config.PipelineConfig`, loaded with `load_config`) instead of being read as a free-form dict. Unknown sections or keys, and missing required keys, raise a `ValidationError` when the `Runner` is created; `Runner.config` is now the validated model. Per-dataset `dates` entries override individual fields of the top-level `dates`. @leifdenby
 - **Breaking:** file path patterns (`datasets.<name>.files` with a `dates:` section, and `alignment.save.path`) now use Python `str.format` syntax instead of earthkit-data patterns: `{reference_time:%Y%m%d%H}` instead of `{reference_time:strftime(%Y%m%d%H)}`, `{year:02d}` instead of `{year:int(%02d)}`. `{lead_time}` (integer hours) and `{valid_time}` are now supported in `files` patterns. `earthkit-data` is no longer a dependency. @michielv
 - **Breaking:** temporal alignment always runs in the pipeline; `alignment.time` is optional and only accepts `lead_time` (`reference` | `intersection` | `union`, forecast reference only). Unknown keys such as `return_as` or `method` now raise an error. `align_time` takes `reference` and an explicit `lead_time` instead of `**kwargs`. @michielv
 - Remove dataset loading and dataset validation and outsource it to [mlwp-data-loaders](https://github.com/mlwp-tools/mlwp-data-loaders) and [mlwp-data-specs](https://github.com/mlwp-tools/mlwp-data-specs) @michielv
diff --git a/README.md b/README.md
index b5c57ff..d359155 100644
--- a/README.md
+++ b/README.md
@@ -43,7 +43,7 @@ For a more comprehensive interactive example, check out the [introductory notebo
 
 ### Configuration Contents
 
-The configuration file is divided into several main sections:
+The configuration file is divided into several main sections. It is validated on load against the schema in `mxalign.pipeline.config` (`PipelineConfig`): unknown sections or keys, and missing required ones such as `alignment.reference`, raise an error up front. Keys that are passed through to a function, such as loader, transformation, metric and save options, are accepted as-is.
 
 ```yaml
 datasets:
diff --git a/examples/advanced.ipynb b/examples/advanced.ipynb
index c577565..b234aa2 100644
--- a/examples/advanced.ipynb
+++ b/examples/advanced.ipynb
@@ -455,7 +455,7 @@
     }
    ],
    "source": [
-    "runner.config()"
+    "runner.config"
    ]
   },
   {
diff --git a/pyproject.toml b/pyproject.toml
index f1a9cee..8a70481 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -23,6 +23,7 @@ dependencies = [
     "mlwp-data-specs",
     "mlwp-data-loaders",
     "pandas>=2.2",
+    "pydantic>=2",
 ]
 
 [project.scripts]
diff --git a/src/mxalign/pipeline/config.py b/src/mxalign/pipeline/config.py
index a4e0682..39b4a6d 100644
--- a/src/mxalign/pipeline/config.py
+++ b/src/mxalign/pipeline/config.py
@@ -1,62 +1,136 @@
+"""Schema for the pipeline YAML config.
+
+Sections and keys not listed here are rejected, except where a model allows
+extra keys (``extra="allow"``); those are passed on as keyword arguments to
+the function the section configures (loader, transformation, metric, save).
+"""
+
+from datetime import datetime
+from typing import Literal
+
 import yaml
+from pydantic import BaseModel, ConfigDict, model_validator
 
 from .dates import Dates
 
 
-def load_yaml(fn: str) -> dict:
-    """Load a YAML file and return its contents as a dict."""
-    with open(fn, "r") as f:
-        return yaml.safe_load(f)
+class _Strict(BaseModel):
+    model_config = ConfigDict(extra="forbid")
+
+
+class _PassThrough(BaseModel):
+    """Model whose unknown keys are kept in ``model_extra`` as function kwargs."""
 
+    model_config = ConfigDict(extra="allow")
 
-class Config:
-    """Pipeline configuration loaded from a YAML file or a plain dict.
+    @property
+    def kwargs(self) -> dict:
+        return dict(self.model_extra or {})
 
-    Top-level ``dates`` entries are merged into each dataset's loader config
-    so that file-path patterns can be expanded to concrete paths.
+
+class DatesConfig(_Strict):
+    """Date range used to expand ``{reference_time}``/``{lead_time}``/``{valid_time}`` in ``files``.
+
+    Every field is optional so a dataset can override part of the top-level
+    ``dates`` section; after merging, all five must be set.
     """
 
-    def __init__(self, config: str | dict) -> None:
-        self.config = load_yaml(config) if isinstance(config, str) else config
-        if not isinstance(self.config, dict):
-            raise TypeError("config should be a dictionary.")
-        self.dates = self.config.pop("dates", None)
-        self._init_datasets()
-        print("Config initialized")
-
-    def __getitem__(self, key: str) -> dict | None:
-        config = self.config.get(key, None)
-        if config:
-            return config.copy()
-        else:
-            return config
-
-    def __call__(self) -> dict:
-        return self.config
-
-    def _init_datasets(self) -> None:
-        for key, loader in self.config["datasets"].items():
-            dates_loader = loader.pop("dates", None)
-            if self.dates:
-                if dates_loader:
-                    keys_all = list(set(self.dates.keys()).union(dates_loader.keys()))
-                    dates = {
-                        key: (
-                            dates_loader[key]
-                            if key in dates_loader.keys()
-                            else self.dates[key]
-                        )
-                        for key in keys_all
-                    }
-                else:
-                    dates = self.dates.copy()
-            else:
-                if dates_loader:
-                    dates = dates_loader.copy()
-                else:
-                    dates = None
-
-            if dates:
-                dates = Dates(**dates)
-                loader["files"] = dates.substitute(loader["files"])
-            self.config["datasets"][key] = loader
+    start: datetime | str | None = None
+    end: datetime | str | None = None
+    period: str | None = None
+    range: str | None = None
+    step: str | None = None
+
+
+class DatasetConfig(_PassThrough):
+    """One entry of ``datasets``; extra keys go to ``load_and_validate_dataset``."""
+
+    loader: str
+    files: str | list[str]
+    variables: str | list[str] | None = None
+    grid_mapping: str | dict | None = None
+    dates: DatesConfig | None = None
+
+
+class TransformationConfig(_PassThrough):
+    """One entry of ``transformations`` (keyed by transformation name); extra keys go to the transformation."""
+
+    datasets: list[str] | None = None
+
+
+class TimeAlignmentConfig(_Strict):
+    lead_time: str | list[str] | None = None
+
+
+class SpaceAlignmentConfig(_Strict):
+    """Interpolator/regridder kwargs, chosen by the kind of space alignment needed."""
+
+    interpolation: dict | None = None
+    regrid: dict | None = None
+
+
+class SaveConfig(_PassThrough):
+    """Output for ``ds.<method>(path, **kwargs)``; extra keys go to the save method."""
+
+    method: str
+    path: str
+
+
+class AlignmentSaveConfig(SaveConfig):
+    datasets: Literal["all", "merge"] = "all"
+
+
+class AlignmentConfig(_Strict):
+    reference: str
+    broadcast_nans: bool = True
+    time: TimeAlignmentConfig | None = None
+    space: SpaceAlignmentConfig | None = None
+    save: AlignmentSaveConfig | None = None
+
+
+class MetricConfig(_PassThrough):
+    """One entry of ``verification.metrics``; extra keys go to the metric function."""
+
+    function: str
+    inputs: dict[str, Literal["forecast", "reference"]]
+
+
+class VerificationConfig(_Strict):
+    reference: str
+    metrics: dict[str, MetricConfig] | None = None
+    save: SaveConfig | None = None
+
+
+class PipelineConfig(_Strict):
+    dates: DatesConfig | None = None
+    datasets: dict[str, DatasetConfig]
+    transformations: dict[str, TransformationConfig] | None = None
+    alignment: AlignmentConfig
+    verification: VerificationConfig | None = None
+
+    @model_validator(mode="after")
+    def _expand_files(self) -> "PipelineConfig":
+        """Expand each dataset's ``files`` pattern(s) over its (merged) ``dates``."""
+        top = self.dates.model_dump(exclude_none=True) if self.dates else {}
+        for name, ds in self.datasets.items():
+            own = ds.dates.model_dump(exclude_none=True) if ds.dates else {}
+            dates = {**top, **own}
+            if not dates:
+                continue
+            missing = set(DatesConfig.model_fields) - dates.keys()
+            if missing:
+                raise ValueError(
+                    f"datasets.{name}: dates is missing {', '.join(sorted(missing))}"
+                )
+            patterns = [ds.files] if isinstance(ds.files, str) else ds.files
+            dates = Dates(**dates)
+            ds.files = [path for p in patterns for path in dates.substitute(p)]
+        return self
+
+
+def load_config(config: str | dict) -> PipelineConfig:
+    """Validate a pipeline config given as a YAML file path or a dict."""
+    if isinstance(config, str):
+        with open(config, "r") as f:
+            config = yaml.safe_load(f)
+    return PipelineConfig.model_validate(config)
diff --git a/src/mxalign/pipeline/runner.py b/src/mxalign/pipeline/runner.py
index 57014b2..080201d 100644
--- a/src/mxalign/pipeline/runner.py
+++ b/src/mxalign/pipeline/runner.py
@@ -3,7 +3,12 @@
 
 from mlwp_data_loaders import load_and_validate_dataset
 
-from .config import Config
+from .config import (
+    PipelineConfig,
+    SpaceAlignmentConfig,
+    TimeAlignmentConfig,
+    load_config,
+)
 from .transformations.transform import transform
 from ..alignment.time import align_time
 from ..alignment.nans import broadcast_nans
@@ -13,7 +18,7 @@
 
 class Runner:
     def __init__(self, config: str | dict):
-        self.config = Config(config)
+        self.config: PipelineConfig = load_config(config)
         self.datasets = {}
 
     def run(self):
@@ -26,16 +31,11 @@ def run(self):
         self.verify()
 
     def load_datasets(self):
-        config = self.config["datasets"]
-        if config is None:
-            raise ValueError("No datasets section in the config.")
-        for name, config_ds in config.items():
-            config_ds = config_ds.copy()
-            loader = config_ds.pop("loader")
-            variables = config_ds.pop("variables", None)
-            grid_mapping = config_ds.pop("grid_mapping", None)
-
-            raw_files = config_ds.pop("files")
+        for name, config_ds in self.config.datasets.items():
+            variables = config_ds.variables
+            grid_mapping = config_ds.grid_mapping
+
+            raw_files = config_ds.files
             if isinstance(raw_files, str):
                 raw_files = [raw_files]
             files = []
@@ -48,8 +48,8 @@ def load_datasets(self):
 
             ds = load_and_validate_dataset(
                 dataset_path,
-                loader=loader,
-                **config_ds,
+                loader=config_ds.loader,
+                **config_ds.kwargs,
             )
 
             if variables is not None:
@@ -61,85 +61,74 @@ def load_datasets(self):
             self.datasets[name] = ds
 
     def transform_datasets(self):
-        config = self.config["transformations"]
-        if config is None:
+        if self.config.transformations is None:
             return
-        for transformation, config_trans in config.items():
-            config_trans = config_trans.copy()
+        for transformation, config_trans in self.config.transformations.items():
             # if no datasets specified, apply to all datasets
-            names_ds = config_trans.pop("datasets", self.datasets.keys())
+            names_ds = config_trans.datasets
+            if names_ds is None:
+                names_ds = self.datasets.keys()
             for name in names_ds:
                 ds = self.datasets[name]
                 self.datasets[name] = transform(
-                    name=transformation, datasets=ds, **config_trans
+                    name=transformation, datasets=ds, **config_trans.kwargs
                 )
 
     def align(self):
-        config = self.config["alignment"]
-        reference = config.pop("reference")
-        brdcst_nans = config.pop("broadcast_nans", True)
-        config_align_time = config.get("time", None)
-        config_align_space = config.get("space", None)
-        config_align_save = config.get("save", None)
+        config = self.config.alignment
+        reference = config.reference
 
         # align in time (always; the time section only holds options)
-        self.align_time(config_align_time, reference_name=reference)
+        self.align_time(config.time, reference_name=reference)
 
         # align in space
-        if config_align_space:
-            self.align_space(reference=reference, config=config_align_space)
+        if config.space is not None:
+            self.align_space(reference=reference, config=config.space)
         else:
             print("Skipping spatial alignment")
 
         # broadcast NaNs
-        if brdcst_nans:
+        if config.broadcast_nans:
             self.datasets = broadcast_nans(self.datasets)
 
         # Save aligned datasets
-        if config_align_save:
-            config = config_align_save.copy()
-            method = config.pop("method")
-            datasets = config.pop("datasets", "all")
-            if datasets == "all":
+        if config.save is not None:
+            save = config.save
+            kwargs = {"path": save.path, **save.kwargs}
+            if save.datasets == "all":
                 for name, ds in self.datasets.items():
-                    save_dataset(method, name, ds, **config)
-            elif datasets == "merge":
+                    save_dataset(save.method, name, ds, **kwargs)
+            elif save.datasets == "merge":
                 ds = xr.concat(
                     self.datasets.values(),
                     dim=xr.Variable("model", list(self.datasets.keys())),
                 )
-                save_dataset(method, "merged", ds, **config)
-            else:
-                raise ValueError("Unknown option for dataset saving.")
+                save_dataset(save.method, "merged", ds, **kwargs)
 
     def verify(self):
-        config = self.config["verification"]
-        reference = self.datasets[config["reference"]]
-        config_metrics = config.get("metrics", None)
-        config_save_metrics = config.get("save", None)
+        config = self.config.verification
+        if config is None:
+            return
+        reference = self.datasets[config.reference]
 
         common_vars = set(reference.data_vars)
         for ds in self.datasets.values():
             common_vars.intersection_update(set(ds.data_vars))
         common_vars = list(common_vars)
 
-        if config_metrics:
+        if config.metrics:
             metrics = {}
-            for metric_name, config_metric in config["metrics"].items():
-                config_metric = config_metric.copy()
-                func_path = config_metric.pop("function")
-                inputs = config_metric.pop("inputs")
-
+            for metric_name, config_metric in config.metrics.items():
                 metric = Metric(
                     name=metric_name,
-                    func_path=func_path,
+                    func_path=config_metric.function,
                     ds_ref=reference[common_vars],
-                    inputs=inputs,
-                    **config_metric,
+                    inputs=config_metric.inputs,
+                    **config_metric.kwargs,
                 )
                 models = {}
                 for ds_name, ds in self.datasets.items():
-                    if ds_name != config["reference"]:
+                    if ds_name != config.reference:
                         models[ds_name] = metric.compute(ds[common_vars])
                 models = xr.concat(
                     models.values(), dim=xr.Variable("model", list(models.keys()))
@@ -150,28 +139,24 @@ def verify(self):
             )
             self.metrics = metrics.transpose("model", "metric", ...).compute()
 
-        if config_save_metrics:
-            config = config_save_metrics.copy()
-            method = config.pop("method")
-            save_metrics(method, self.metrics, **config)
-
-    def align_time(self, config, reference_name=None):
-        config = dict(config or {})
-        lead_time = config.pop("lead_time", None)
-        if config:
-            raise ValueError(
-                f"Unknown option(s) in alignment.time: {', '.join(config)}. "
-                "Only lead_time is supported."
-            )
+        if config.save is not None:
+            save = config.save
+            save_metrics(save.method, self.metrics, path=save.path, **save.kwargs)
+
+    def align_time(
+        self, config: TimeAlignmentConfig | None, reference_name: str | None = None
+    ):
+        lead_time = config.lead_time if config is not None else None
         self.datasets = align_time(
             self.datasets, reference=reference_name, lead_time=lead_time
         )
 
-    def align_space(self, reference, config):
+    def align_space(self, reference: str, config: SpaceAlignmentConfig):
         ds_ref = self.datasets[reference]
         for name, ds in self.datasets.items():
             if name != reference:
-                options = config.get(get_spatial_alignment(ds, ds_ref), {})
+                kind = get_spatial_alignment(ds, ds_ref)
+                options = getattr(config, kind, None) or {}
                 self.datasets[name] = ds.mx.align_space_with(ds_ref, **options)
 
 
diff --git a/tests/test_config.py b/tests/test_config.py
new file mode 100644
index 0000000..dd5fbda
--- /dev/null
+++ b/tests/test_config.py
@@ -0,0 +1,75 @@
+from pathlib import Path
+
+import pytest
+from pydantic import ValidationError
+
+from mxalign.pipeline.config import load_config
+
+EXAMPLE_CONFIG = Path(__file__).parent.parent / "examples" / "config.yaml"
+
+DATES = dict(start="2020-01-01", end="2020-01-02", period="1D", range="12h", step="12h")
+
+
+def _config(**sections) -> dict:
+    return {
+        "datasets": {"fc": {"loader": "x", "files": "/d/fc.nc"}},
+        "alignment": {"reference": "fc"},
+        **sections,
+    }
+
+
+def test_example_config_validates():
+    config = load_config(str(EXAMPLE_CONFIG))
+    assert config.alignment.reference == "cerra"
+    assert config.alignment.space.interpolation == {"method": "delaunay"}
+    assert config.verification.metrics["rmse"].kwargs == {
+        "dim": ["reference_time", "grid_index"],
+        "skipna": True,
+    }
+    # files patterns are expanded over the dates section
+    assert len(config.datasets["la-1024-ea-00"].files) > 1
+
+
+def test_unknown_top_level_key_is_rejected():
+    with pytest.raises(ValidationError, match="not_a_section"):
+        load_config(_config(not_a_section={"reference": "fc"}))
+
+
+def test_missing_alignment_reference_is_rejected():
+    config = _config()
+    config["alignment"] = {"broadcast_nans": False}
+    with pytest.raises(ValidationError, match="alignment.reference"):
+        load_config(config)
+
+
+def test_unknown_save_datasets_option_is_rejected():
+    save = {"method": "to_netcdf", "path": "out.nc", "datasets": "some"}
+    with pytest.raises(ValidationError, match="alignment.save.datasets"):
+        load_config(_config(alignment={"reference": "fc", "save": save}))
+
+
+def test_extra_dataset_keys_are_passed_to_loader():
+    config = _config()
+    config["datasets"]["fc"]["chunks"] = {"time": 1}
+    assert load_config(config).datasets["fc"].kwargs == {"chunks": {"time": 1}}
+
+
+def test_dataset_dates_override_top_level_dates():
+    config = _config(dates=DATES)
+    config["datasets"]["fc"] = {
+        "loader": "x",
+        "files": "/d/{reference_time:%Y%m%d}.nc",
+        "dates": {"end": "2020-01-03"},
+    }
+    assert load_config(config).datasets["fc"].files == [
+        "/d/20200101.nc",
+        "/d/20200102.nc",
+        "/d/20200103.nc",
+    ]
+
+
+def test_incomplete_dates_are_rejected():
+    config = _config()
+    config["datasets"]["fc"]["dates"] = {"start": "2020-01-01"}
+    with pytest.raises(ValidationError, match="dates is missing end, period"):
+        load_config(config)
diff --git a/tests/test_dates.py b/tests/test_dates.py
index c37a6bb..441eac5 100644
--- a/tests/test_dates.py
+++ b/tests/test_dates.py
@@ -2,7 +2,7 @@
 
 import pytest
 
-from mxalign.pipeline.config import Config
+from mxalign.pipeline.config import load_config
 from mxalign.pipeline.dates import Dates
 from mxalign.pipeline.save import DatasetPath
 
@@ -45,15 +45,16 @@ def test_substitute_lead_time_requires_whole_hours():
 
 def test_config_expands_files_from_dates_section():
     # YAML parses unquoted timestamps to datetime objects
-    config = Config(
+    config = load_config(
         {
             "dates": {**DATES, "start": datetime.datetime(2020, 1, 1)},
             "datasets": {
                 "fc": {"loader": "x", "files": "/d/{reference_time:%Y%m%d}.nc"}
             },
+            "alignment": {"reference": "fc"},
         }
     )
-    assert config["datasets"]["fc"]["files"] == [
+    assert config.datasets["fc"].files == [
         "/d/20200101.nc",
         "/d/20200102.nc",
         "/d/20200103.nc",
diff --git a/tests/test_runner.py b/tests/test_runner.py
index b3aa11d..d84eded 100644
--- a/tests/test_runner.py
+++ b/tests/test_runner.py
@@ -1,4 +1,5 @@
 import pytest
+from pydantic import ValidationError
 
 from mxalign.pipeline.runner import Runner
 
@@ -19,10 +20,14 @@ def test_align_runs_time_alignment_without_time_section(ds_fcst, ds_obs):
     assert runner.datasets["obs"].mx.is_forecast()
 
 
-def test_align_time_rejects_unknown_options(ds_fcst, ds_obs):
-    runner = _runner({"fcst": ds_fcst, "obs": ds_obs}, {"reference": "obs"})
-    with pytest.raises(ValueError, match="Unknown option.*return_as"):
-        runner.align_time({"return_as": "forecast"}, reference_name="obs")
+def test_align_time_rejects_unknown_options():
+    with pytest.raises(ValidationError, match="alignment.time.return_as"):
+        Runner(
+            {
+                "datasets": {},
+                "alignment": {"reference": "obs", "time": {"return_as": "forecast"}},
+            }
+        )
 
 
 def test_transform_datasets_without_transformations_section(ds_obs):
diff --git a/uv.lock b/uv.lock
index 6ce6399..1e99d4f 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1,5 +1,5 @@
 version = 1
-revision = 5
+revision = 3
 requires-python = ">=3.12"
 resolution-markers = [
     "python_full_version >= '3.14' and sys_platform == 'win32'",
@@ -204,6 +204,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/fb/76/641ae371508676492379f16e2fa48f4e2c11741bd63c48be4b12a6b09cba/aiosignal-1.4.0-py3-none-any.whl", hash = "sha256:053243f8b92b990551949e63930a839ff0cf0b0ebbe0597b0f3fb19e1a0fe82e", size = 7490, upload-time = "2025-07-03T22:54:42.156Z" },
 ]
 
+[[package]]
+name = "annotated-types"
+version = "0.8.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/5f/56/a8120250d128bed162cd73c76d45f6ef9991f3e068f62a8ee060afa3104a/annotated_types-0.8.0.tar.gz", hash = "sha256:13b2beaad985e05e2d6407ee4c4f35590b11f8d693a258a561055cac8f64cab7", size = 15893, upload-time = "2026-07-23T20:16:13.995Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/99/91/8acff4f5e50511b911bbccb72b8628a49c68ce14148cd9f6431094859a90/annotated_types-0.8.0-py3-none-any.whl", hash = "sha256:f072f4d804ea359e4eaf198b1af7a8b0943881a87f31bb764f8bf219bb9419e0", size = 13427, upload-time = "2026-07-23T20:16:12.938Z" },
+]
+
 [[package]]
 name = "appnope"
 version = "1.0.0"
@@ -1808,6 +1817,7 @@ dependencies = [
     { name = "mlwp-data-specs" },
     { name = "netcdf4" },
     { name = "pandas" },
+    { name = "pydantic" },
     { name = "pyyaml" },
     { name = "scipy" },
     { name = "xarray" },
@@ -1853,6 +1863,7 @@ requires-dist = [
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     { name = "netcdf4", specifier = ">=1.7.4" },
     { name = "pandas", specifier = ">=2.2" },
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     { name = "scipy", specifier = ">=1.17.0" },
     { name = "xarray", specifier = ">=2026.1.0" },
@@ -2125,7 +2136,7 @@ name = "pexpect"
 version = "4.9.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
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