The race condition occurs because multiple threads can access and modify the shared dictionaries (`self.jobs` and `self.results`) simultaneously without synchronization. Specifically, two threads could check if a job exists, process it, and then both attempt to write the result and delete the job, leading to data corruption or lost updates.

To fix this, we need to use a `threading.Lock` to ensure that only one thread can execute the critical sections of code (accessing/modifying shared state) at a time.

Here is the complete fixed implementation:

```python
import threading

class JobQueue:
    def __init__(self):
        self.jobs = {}
        self.results = {}
        # Initialize a lock to synchronize access to shared state
        self.lock = threading.Lock()

    def add_job(self, job_id, data):
        # Protecting add_job ensures thread-safe insertion into the dictionary
        with self.lock:
            self.jobs[job_id] = data
        return job_id

    def process_job(self, job_id, processor):
        # Acquire the lock to ensure atomicity of the check, read, write, and delete operations.
        # This prevents multiple threads from processing the same job simultaneously.
        with self.lock:
            if job_id not in self.jobs:
                return False

            data = self.jobs[job_id]
            
            # Note: We hold the lock during processing. While this serializes execution 
            # (only one job processed at a time), it is the safest direct fix for the 
            # provided logic structure. 
            # For higher performance, one could 'pop' the job here, release the lock, 
            # process, and then re-acquire the lock to store the result.
            result = processor(data)

            self.results[job_id] = result
            del self.jobs[job_id]
        
        return True

    def get_result(self, job_id):
        # Protecting get_result ensures we read a consistent state
        with self.lock:
            return self.results.get(job_id)
```

### Key Changes:
1.  **`self.lock = threading.Lock()`**: Added in `__init__` to create a synchronization primitive.
2.  **`with self.lock:`**: Used the context manager pattern in all methods to automatically acquire and release the lock.
    *   **`add_job`**: Locked to prevent race conditions if multiple jobs are added concurrently.
    *   **`process_job`**: Locked to ensure that the check (`if job_id not in self.jobs`), the read, the processing, the result write, and the deletion happen atomically. This prevents the specific race condition where two threads might process the same job ID and overwrite each other's results.
    *   **`get_result`**: Locked to ensure thread-safe reading of the results dictionary.