To solve the given optimization problem using Gurobi, we need to translate the natural language description into a mathematical model and then implement this model in Python using the Gurobi library.

The objective function is to maximize \(4 \times (\text{hours worked by Dale})^2 + 6 \times (\text{hours worked by Dale}) \times (\text{hours worked by Hank}) + 7 \times (\text{hours worked by Dale})\).

The constraints are:
1. The computer competence rating for Dale is 4.
2. The computer competence rating for Hank is 4.
3. The total combined computer competence rating from hours worked by Dale and Hank should be at least 29.
4. \(-8 \times (\text{hours worked by Dale}) + 6 \times (\text{hours worked by Hank}) \geq 0\).
5. The total combined computer competence rating from hours worked by Dale and Hank should not exceed 70.

Given the variables:
- \(D\) = hours worked by Dale
- \(H\) = hours worked by Hank

And given the attributes:
- Computer competence ratings for Dale and Hank are both 4.

We can model the problem as follows:

Maximize: \(4D^2 + 6DH + 7D\)

Subject to:
1. \(4D + 4H \geq 29\) (Combined minimum computer competence rating)
2. \(-8D + 6H \geq 0\) (Linear constraint)
3. \(4D + 4H \leq 70\) (Combined maximum computer competence rating)

Since the problem does not require \(D\) or \(H\) to be integers, we treat them as continuous variables.

Here is how you can implement this in Gurobi using Python:

```python
from gurobipy import *

# Create a new model
m = Model("Optimization_Problem")

# Define the variables
D = m.addVar(lb=0, name="hours_worked_by_Dale")
H = m.addVar(lb=0, name="hours_worked_by_Hank")

# Set the objective function
m.setObjective(4*D**2 + 6*D*H + 7*D, GRB.MAXIMIZE)

# Add constraints
m.addConstr(4*D + 4*H >= 29, name="min_computer_rating")
m.addConstr(-8*D + 6*H >= 0, name="linear_constraint")
m.addConstr(4*D + 4*H <= 70, name="max_computer_rating")

# Optimize the model
m.optimize()

# Print solution
if m.status == GRB.OPTIMAL:
    print("Optimal solution found:")
    print(f"Hours worked by Dale: {D.x}")
    print(f"Hours worked by Hank: {H.x}")
    print(f"Objective function value: {m.objVal}")
else:
    print("No optimal solution found")
```