Professional work journal
Student’s Name
Institution
, PROFESSIONAL WORK JOURNAL 2
In week three, I outlined and described the components that I would work on during that
session to help improve my professional portfolio. As data engineer there are various
components that I focused on during the session to help improve my portfolio as an engineer.
An engineering portfolio is a treasured instrument when searching for an engineering job in the
job market. The employ of engineering portfolios as an element of a job search addresses
developing patterns in business and education. Whereas the hunt of an education is mainly an
personal “self-centered” action, employment in a firm is team-based. There are five forms of
communication that an engineer needs and that is the key component that I focused on during the
session. The five comprise mathematical, writing, graphical, speaking as well as listening
(Sugandi, 2017). Creative means need to be found to demonstrate that an engineer has mastered
all of these kinds of communication. A design case wherein mathematics is overtly employed to
communicate the solution or problem, remarkable data generated completed by the engineer or a
real video tape of a speech and a certificate for attendance at a "listening efficacy" workshop are
instances showing mastery of the objectives. By the end of the session I had almost perfected the
five forms communication that an engineer, including data engineer needs hence improving my
professional portfolio.
In my week 4, the task was to come up with 3 to 5 questions for my interview as regards
my subject’s position, responsibilities and practices. Some of the questions I prepared comprise:
Can you recall a time when you disagreed with your supervisor? How did you handle it? and
What safeguards do you have in position to double-check your engineering work and ensure that
mistakes do not go past you? While preparing the questions, I got to learn more about questions
that data engineers in the course of their interviews. I came across many interview questions that
caused me to see my data career from wider point of view than the one had before. Actually,