Use Kafka Connect to update Elasticsearch field on existing document instead of creating new

I have Kafka set-up running with the Elasticsearch connector and I am successfully indexing new documents into an ES index based on the incoming messages on a particular topic.

However, based on incoming messages on another topic, I need to append data to a field on a specific document in the same index.

Psuedo-schema below:

{
   "_id": "6993e0a6-271b-45ef-8cf5-1c0d0f683acc",
   "uuid": "6993e0a6-271b-45ef-8cf5-1c0d0f683acc",
   "title": "A title",
   "body": "A body",
   "created_at": 164584548,
   "views": []
}

^ This document is being created fine in ES based on the data in the topic mentioned above.

However, how do I then add items to the views field using messages from another topic. Like so:

article-view topic schema:

{
   "article_id": "6993e0a6-271b-45ef-8cf5-1c0d0f683acc",
   "user_id": 123456,
   "timestamp: 136389734
}

and instead of simply creating a new document on the article-view index (which I dont' want to even have). It appends this to the views field on the article document with corresponding _id equal to article_id from the message.

so the end result after one message would be:

{
   "_id": "6993e0a6-271b-45ef-8cf5-1c0d0f683acc",
   "uuid": "6993e0a6-271b-45ef-8cf5-1c0d0f683acc",
   "title": "A title",
   "body": "A body",
   "created_at": 164584548,
   "views": [
       {
           "user_id": 123456,
           "timestamp: 136389734
       }
   ]
}

Using the ES API it is possible using a script. Like so:

{
    "script": {
        "lang": "painless",
        "params": {
            "newItems": [{
                "timestamp": 136389734,
                "user_id": 123456
            }]
        },
        "source": "ctx._source.views.addAll(params.newItems)"
    }
}

I can generate scripts like above dynamically in bulk, and then use the helpers.bulk function in the ES Python library to bulk update documents this way.

Is this possible with Kafka Connect / Elasticsearch? I haven't found any documentation on Confluent's website to explain how to do this.

It seems like a fairly standard requirement and an obvious thing people would need to do with Kafka / A sink connector like ES.

Thanks!