Databricks schedules use Quartz cron, which has no way to say "every 14 days". Cron fields only match calendar positions (day-of-week, day-of-month), so you can't alternate weeks reliably. Patterns like 1,15,29 on days of the month drift and break at month boundaries.

Recommended: run weekly, skip alternate weeks with a gate task

Schedule the job every Wednesday, and add a first task that decides whether this is an "on" week. Downstream tasks run only if it says yes.

1. Schedule weekly (Quartz cron):

yaml
schedule:
quartz_cron_expression: "0 0 6 ? * WED *" # every Wednesday 06:00
timezone_id: "Asia/Kolkata" # set to your timezone
pause_status: UNPAUSED

2. Gate notebook (check_week): use an anchor date instead of ISO week numbers, since ISO week parity breaks at year boundaries (52/53-week years):

python
from datetime import date

ANCHOR = date(2026, 10, 7) # a Wednesday that SHOULD run; change as needed
weeks_since = (date.today() - ANCHOR).days // 7
should_run = (weeks_since % 2 == 0)

dbutils.jobs.taskValues.set(key="should_run", value=str(should_run).lower())

3. Wire it up with a condition task:

yaml
tasks:
- task_key: check_week
notebook_task:
notebook_path: jobs/base/CHECK_WEEK
source: GIT

- task_key: is_run_week
depends_on:
- task_key: check_week
condition_task:
op: EQUAL_TO
left: "{{tasks.check_week.values.should_run}}"
right: "true"

- task_key: main_processing
depends_on:
- task_key: is_run_week
outcome: "true"
notebook_task:
notebook_path: jobs/base/MAIN_PROCESSING
source: GIT

On "off" weeks, main_processing is shown as excluded and the run finishes successfully, with no failure alerts. The gate adds only a few seconds of compute, and you can run it on a small job cluster.

Alternative options

Databricks periodic trigger (trigger.periodic with interval: 2, unit: WEEKS). It does repeat every 2 weeks, but it isn't anchored to a weekday or time. It counts from when the job is created or saved, so you'd have to deploy it on the right Wednesday. Redeploying or editing the job can shift the cycle, so it's fragile in production.

Azure Data Factory (since you already use it). A Schedule trigger supports frequency: Week, interval: 2, weekDays: ["Wednesday"], with a startTime on the first run date. ADF then calls the Databricks job via the Jobs API or a Databricks activity. This is clean if ADF is already your orchestrator.

Two separate jobs or schedules: some teams use cron on specific dates, like 0 0 6 1,15,29 * ?, but this is not actually alternate Wednesdays and I don't recommend it.