I got a verbal offer from Amazon for Applied Scientist L5. I have 8 years of experience after my PhD, and I was clear with the recruiter that I only interview for L6, and I think I did pretty well in my interviews. I understand that the level is based on the performance in the interviews, and I know that tech companies love to down-level, but I'm bummed about L6 -> L5 thing.

Has anybody here been successful to negotiate with Amazon to up-level after receiving the initial offer?

The Situation:

I 18(M) in the UK want to do a tech apprenticeship, I have had two FAANG company offers, but can't decide which one to pick. I've created a pros/cons list of all the different aspects of the two offers. Everything mentioned below about career predictions etc. is my opinion influenced by various people and sources so I'm happy to hear from anyone who disagrees with any of the points made or wants a further explanation if I haven't explained it properly (I kinda wrote this while my brain was in overdrive). Any other advice is also appreciated!

Breakdown Of Offers:

Google - Level 4 (Foundation Degree) Software Engineering Apprenticeship For 2 years in Central London

• Qualification in Software Engineering Amazon - Level 6 (degree) Data Analytics Apprenticeship For 3 Years in Central London

• Qualification in Digital And Technology Solutions (Data Pathway)

Breakdown Of Salaries (not a deciding factor for me at this point):

Google:

• 1st year: £37,000 (£30k base + £7k relocation)

• 2 year: £32,000 (£32k base)

• 3rd year: who knows? Could be a lot more or a lot less

Amazon (full compensation as salary):

• 1st year: £32,500

• 2nd year: £33,500 (Could be a £2k increase but currently £1k)

• 3rd Year £34,500 (Could be a £2k increase but currently £1k)

Software Engineering Vs Data Science

Software Engineering:

• Better Job Opportunities

• Better Pay (generally, not a big difference in big tech)

• More Defined Career Path

• More Secure Job

• Skillset required is more straightforward

• Unlikely to dramatically increase or decrease in market size

• Background In Software is helpful in data as well

• Better suited to move into machine learning

Data Science:

• In my apprenticeship, I am a data analyst not scientist, however my manager has said I can do more data science/engineering based work to help me prepare for that

• Smaller Job Market

• Same Pay as SWE in big tech, but less pay elsewhere

• Less defined Career Path, development ceiling tends to be lower and only allows for movement into manager positions after Senior positions

• Less secure Job

• Much more varied skillset required, understanding of in-depth mathematical, business, and computer science concepts required, and is needed to be shown in interviews

  • But this extra understanding is not compensated for with a higher salary, essentialy more work and learning for not more pay

  • However Varied skillset does suit my personality, I am quite varied, and interested in all the aspects of data

  • Possibility of excelling in communication skills and making it my stand out feature in the future, able to articulate and convey data intelligence to non-technical stakeholders. This is also true in SWE but may have more of an impact in Data, however I could definitely simply decide to be a more customer-focused SWE and probably still be able to highlight the same skillset

• IMO market is a lot more volatile, could explode in size further due to A.I, or more likely shrink massively in demand. as described in this post: [ Data Science is a fad (Cynical Post #2334) : datascience (reddit.com)]

• Data isn't really required in software engineering, so not helpful if I then what to switch over, no measurable benefit to doing data first.

• Can move into machine learning but would be better for me to focus more on data engineering during my apprenticeship then.

Benefits of the degree at Amazon:

• degree is a degree

• Certain companies still require a degree (or more) for tech roles, and even if they don't require it, I'm considering the fact that some companies might simply filter out applicants who don't have a degree.

  • From what I can tell, this is something that matters less in mid-level/senior positions, as they don't tend to mention it as much in job descriptions, whereas almost all junior postings mention a requirement for a degree.

• May help with getting a visa if I wish to move abroad (I do plan on moving to America at some point in the future)

• Can go on to do a masters from a more prestigious university (I Did have an offer from Imperial College London to study a Computing degree but decided an apprenticeship was better)

Reasons For Google:

• Google (THE BIG REASON)

• Software Engineering

• Benefits (free food, gym, swimming pool, learning reimbursement etc, makes more of a difference at my salary level and living costs in London)

• Only 2 years - graduate to proper job faster if I can get one

• Possible job afterwards at Google

• Training towards interviews after graduation

• Better Projects to work on

• More interesting people

• Better work environment from what I've seen and heard so far

• Smaller number of SWE apprentices (around 10-12) in my cohort, could be a positive or negative I'm not sure yet.

Reasons For Amazon:

• Degree (THE BIG REASON)

• More established Apprenticeship network - been running them for 10 years now, and are hiring a much larger number of apprentices that Google.

• large number of my team will be apprentices in September, so a great learning environment hopefully

• Have already met my manager and am optimistic about my relationship with her, she is very experienced in the analytics field.

• 3 years - so more prepared for a job afterwards

• Although job isn't guranteed at amazon either, it's much more likely to be able to get one, support provided to find the best job

• Could pivot from data analyst into software if I feel that will be better suited, and still have a degree, opportunity cost probably wouldn't be huge at such an early stage in my career.

• I feel I'd be more employable to companies other than amazon, whereas at Google, other big tech companies might still be hesitant to hire someone with only 2 years experience.

Once again thank you everyone!