# Data Engineer Jobs at US Startups and Mid-Size Companies

**Use case:** 

US data engineer postings from the last 30 days at employers with up to 1,000 employees, staffing agencies and aggregators removed, with title, employer, location, seniority, salary where stated, applicants and recruiter. The employer hiring signal adds each company's open postings and its last 7, 30 and 90 days. For job boards, recruiting and tracking which startups build data teams.

## Input

```json
{
  "titleSearch": [
    "\"data engineer\""
  ],
  "locationSearch": [
    "United States"
  ],
  "limit": 100,
  "previewOnly": false,
  "compact": false,
  "timeRange": "30d",
  "organizationEmployeesLte": 1000,
  "removeAgency": true,
  "hasSalary": false,
  "salaryCurrency": "USD",
  "recruiterOnly": false,
  "status": "active",
  "recruiter": "card",
  "employerHiring": true,
  "decisionMakers": false,
  "decisionMakersPerCompany": 3,
  "descriptionType": "text"
}
```

## Output

```json
{
  "_status": {
    "label": "Status",
    "format": "string"
  },
  "_type": {
    "label": "Row type",
    "format": "string"
  },
  "_input": {
    "label": "Input",
    "format": "object"
  },
  "title": {
    "label": "Job title",
    "format": "string"
  },
  "companyName": {
    "label": "Company",
    "format": "string"
  },
  "locationText": {
    "label": "Location",
    "format": "string"
  },
  "postedAt": {
    "label": "Posted",
    "format": "string"
  },
  "seniorityLevel": {
    "label": "Seniority",
    "format": "string"
  },
  "employmentTypeName": {
    "label": "Employment type",
    "format": "string"
  },
  "salaryText": {
    "label": "Salary",
    "format": "string"
  },
  "applicantRange": {
    "label": "Applicants",
    "format": "string"
  },
  "recruiterName": {
    "label": "Recruiter",
    "format": "string"
  },
  "url": {
    "label": "Job",
    "format": "string"
  },
  "_note": {
    "label": "Note",
    "format": "string"
  },
  "_error": {
    "label": "Details",
    "format": "string"
  }
}
```

## How it works

### 1. Sign up on Apify or log in

The LinkedIn Jobs Database API — Advanced Search + Decision Makers Actor is ready to run with the inputs already set for "Data Engineer Jobs at US Startups and Mid-Size Companies". [Sign up or log in](https://console.apify.com/create-task-from-example/th3xpexcfrVPdBhaP) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Data Engineer Jobs at US Startups and Mid-Size Companies" task

The LinkedIn Jobs Database API — Advanced Search + Decision Makers Actor will start running based on the input automatically. You can also change all the input fields, like title search, location search, and more, to match your specific use case.

### 3. Receive the "Data Engineer Jobs at US Startups and Mid-Size Companies" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as status, row type, input, and more.

### 4. Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also [run the "Data Engineer Jobs at US Startups and Mid-Size Companies" task via API](https://apify.com/b2bsearch/linkedin-job-search-api.md).

## FAQ

### What does the data engineer jobs task return?

The data engineer jobs task returns US postings from the last 30 days at employers with up to 1,000 staff: title, employer, location, posting date, seniority, salary where stated, applicants, recruiter and the job link.

### Why remove staffing agencies?

Agencies and aggregators repost the same role many times. Remove agencies in the data engineer jobs task drops them by industry and by the employer's own card, so every row is a direct employer.

### What is the employer hiring signal?

With Employer hiring on, each row of the data engineer jobs task carries the employer's open postings and postings in the last 7, 30 and 90 days, telling a company scaling a team from a one-off hire.

### How do I get a daily feed of new postings?

Schedule the data engineer jobs task daily with Time range 24h, or set Posted after to the date of the last run. Every row says what date the data runs to.

## About this Actor

This example demonstrates how to use [LinkedIn Jobs Database API — Advanced Search + Decision Makers](https://apify.com/b2bsearch/linkedin-job-search-api.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/b2bsearch/linkedin-job-search-api.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/b2bsearch/linkedin-job-search-api.md

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).