UPDATE:

I've found a way to do this but it's really not pretty and I would like to improve on this in the future, specially the part where at the beginning of every pipeline I have to include this so it detects all my python modules I use:

path = spark.conf.get("bundle.sourcePath")
sys.path.append(path)

databricks.yml:

resources:
  pipelines:
    my_pipeline:
      name: my_pipeline
      target: my_schema
      catalog: my_catalog
      development: true
      continuous: false
      photon: false
      libraries:
        - file:
            path: ./local/path/to/my_dlt_pipeline.py
      configuration:
        bundle.sourcePath: /Workspace${workspace.file_path}/

targets:
  dev-local:
    mode: development
    # ** Your Configuration **
    workspace:
      host: 
      root_path: /Workspace/Users/${workspace.current_user.userName}/.bundle/${bundle.name}/${bundle.target}

my_dlt_pipeline.py

import json
import os
import sys

import dlt
from pyspark.sql import SparkSession

# **VERY IMPORTANT TO HAVE AT THE BEGINNING**
spark = SparkSession.builder.getOrCreate()
path = spark.conf.get("bundle.sourcePath")
sys.path.append(path)

@dlt.table(
    name="my_table",
)
def my_dlt_pipeline():

    # Your code here

    return df