Lever is a cloud-based recruiting software platform. It provides tools to source, nurture, interview, and hire job candidates, with both an applicant tracking system (ATS) and CRM functionality, along with analytics that provide insights into things such as cost and engagement.

Amazon QuickSight is the AWS business intelligence tool for creating dashboards and visualizations. Users are charged per session only for the time when they access dashboards or reports. QuickSight supports a variety of data sources, such as individual databases (Amazon Aurora, MariaDB, and Microsoft SQL Server), data warehouses (Amazon Redshift and Snowflake), and SaaS sources (Adobe Analytics, GitHub, and Salesforce), along with several common standard file formats.

Lever provides a RESTful API that lets developers fetch information about postings, candidates, interviews, and other items stored in the platform. For example, to retrieve information about a specific posting, you would call GET https://api.lever.co/v1/postings/posting-ID.

Here's an example of the kind of response you might see with a query like the one above.

{
  "data": {
    "id": "f2f01e16-27f8-4711-a728-7d49499795a0",
    "text": "Infrastructure Engineer",
    "createdAt": 1407779365624,
    "updatedAt": 1407779365624,
    "user": "ec1cb1bb-8b58-4834-bc6e-b2af06296e4a",
    "owner": "ec1cb1bb-8b58-4834-bc6e-b2af06296e4a",
    "hiringManager": "ec1cb1bb-8b58-4834-bc6e-b2af06296e4a",
    "confidentiality": "non-confidential",
    "categories": {
      "team": "Platform",
      "department": "Engineering",
      "location": "San Francisco",
      "commitment": "Full-time",
      "level": "Senior"
    },
    "content": {
      "description": "The Infrastructure Engineer will act as...\\nSuperman.",
      "descriptionHtml": "
The Infrastructure Engineer will act as...
Superman.
",
      "lists": [
        {
          "text": "Job requirements",
          "content": "
Quick learner
Ambitious
"
        }
      ],
      "closing": "Our company is proud to be an equal opportunity workplace.",
      "closingHtml": "
Our company is proud to be an equal opportunity workplace.
"
    },
    "tags": [],
    "state": "published",
    "distributionChannels": [
      "internal",
      "public"
    ],
    "reqCode": "7381912",
    "requisitionCodes": [
      "7381912"
    ],
    "urls": {
      "list": "https://jobs.lever.co/example",
      "show": "https://jobs.lever.co/example/f2f01e16-27f8-4711-a728-7d49499795a0/",
      "apply": "https://jobs.lever.co/example/f2f01e16-27f8-4711-a728-7d49499795a0/apply"
    }
  }
}

If you don't already have a data structure in which to store the data you retrieve, you'll have to create a schema for your data tables. Then, for each value in the response, you'll need to identify a predefined datatype (INTEGER, DATETIME, etc.) and build a table that can receive them. The Lever documentation should tell you what fields are provided by each endpoint, along with their corresponding datatypes.

Complicating things is the fact that the records retrieved from the source may not always be "flat" — some of the objects may actually be lists. In these cases you'll likely have to create additional tables to capture the unpredictable cardinality in each record.

You must replicate data from your SaaS applications to a data warehouse (such as Redshift) before you can report on it using QuickSight. Once you specify a data source you want to connect to, you must specify a host name and port, database name, and username and password to get access to the data. You then choose the schema you want to work with, and a table within that schema. You can add additional tables by specifying them as new datasets from the main QuickSight page.

QuickSights provides both a visual report builder and the ability to use SQL to select, join, and sort data. QuickSight lets you combine visualizations into dashboards that you can share with others, and automatically generate and send reports via email.

At this point you've coded up a script or written a program to get the data you want and successfully moved it into your data warehouse. But how will you load new or updated data? It's not a good idea to replicate all of your data each time you have updated records. That process would be painfully slow and resource-intensive.

The key is to build your script in such a way that it can identify incremental updates to your data. Thankfully, Lever's API results include fields like createdAt and updatedAt that allow you to identify records that are new since your last update (or since the newest record you've copied). Once you've taken new data into account, you can set your script up as a cron job or continuous loop to keep pulling down new data as it appears.