# Hiring a data engineer vs working with a data partner | Silicon

URL: https://meetsilicon.com/blog/hiring-a-data-engineer-vs-working-with-a-data-partner/

> What a high-growth startup gets from hiring its first data engineer, bringing in a consultant or working with a data partner, with the time and cost of each.

Guides Hiring a data engineer vs working with a data partner
Most startups start thinking about a data hire after a specific moment. The board asks for revenue by plan and three people send three different numbers, or the founder spends a weekend rebuilding a spreadsheet before an investor update. By then the company runs on a dozen apps, and nobody owns the work of bringing their data into one place.
There are three common ways to get that work done. You can hire a data engineer, bring in a consultant for a project, or work with a data partner. Each suits a different company, and the time and cost differ more than most founders expect.
## Option 1: Hire your first data engineer
A data engineer connects the company's apps, brings the data into one place and keeps it up to date. Many startups hire an analytics engineer instead, who also defines the key metrics and builds the first dashboards.
The main cost is time. KORE1, a recruiting firm, puts the internal search for one data engineer at 6-10 weeks, followed by two to four months of ramp-up, so a company typically waits five to seven months from the decision to reliable data (KORE1). One senior analytics engineer and the tools they need cost about $120-227k a year at a company of around $5M revenue (Valiotti).
A single hire also means the knowledge of how every number is built sits with one person. When they take a holiday or leave, requests wait.
Hiring makes sense when data is part of the product itself, when you need someone in the room every day, or when there are already more requests than one person outside the company could handle.
## Option 2: Bring in a data analytics consultant
A consultant is usually hired for a project with an end date, such as reporting for a fundraise or a move off an old reporting tool. Good consultants work quickly because they have done the same setup many times.
The difficulty comes after the project ends. Metric definitions need updating when pricing or plans change, new apps get added, and dashboards break when something in the data changes. Unless someone on your team takes the work over, the setup starts to drift within a few months, and the next fix is a new contract.
A consultant fits well when you already have a data team that can maintain the work, or when you need specialist work beyond reporting, such as a pricing model. There is a longer comparison on our Silicon vs hiring a data analytics consultant page.
## Option 3: Work with a data partner
A data partner builds your data foundation and keeps maintaining it as the company grows. At Silicon, that means connecting the apps your company runs on, defining each key metric with the person who owns it, and setting up dashboards and an AI analyst that anyone can ask in Slack. After launch, requests from any team go to a shared channel, and we update the definitions when pricing, plans or tools change.
The foundation is usually live in about ten weeks, which is shorter than the time it takes to hire and ramp up one engineer. Our AI analytics platform checks each change to your data and flags the dashboards it affects, and we make the fix.
A data partner suits companies with no data team, or with one data person answering requests from every team. If you later build your own data team, they start from documented metric definitions and data models. More detail is on the data partnership page.
## How the three compare
| Hire a data engineer | Data analytics consultant | Data partner
Time to reliable data | 5-7 months, including hiring and ramp-up | A few weeks, for the project's scope | About ten weeks for the foundation
After launch | One person maintains it | Handed over to your team | Maintained as the company grows
Cost | About $120-227k a year, with tools | Hourly, daily or per project | A fixed-scope build, then monthly or annual
When someone leaves | Much of the knowledge leaves with them | Depends on the handover | Definitions are documented and the partner covers the work
## How to decide
Three questions usually settle it.
- Is there someone who will maintain the data after it is set up? If not, a one-off project tends to drift, and a hire or a partner is the safer choice.
- How soon do you need reliable numbers? If a fundraise or board meeting is less than six months away, a first hire is unlikely to be ready in time.
- Is data part of what you sell, or does it run the business? Products built on data usually need engineers in-house. For reporting, key metrics and everyday questions from each team, a partner can cover the work.
If you're weighing these options, talk to Sujay, the founder, about your setup. If one person can still keep track of every number by hand, we'll tell you it's too early on the first call.
FAQ
## Frequently asked questions
### Should a startup's first data hire be a data engineer or a data analyst? +
If nobody has connected the company's data yet, a data engineer or analytics engineer usually comes first, because an analyst needs reliable data to work from. If the data is already in one place and each key metric is defined, an analyst can start answering questions straight away.
### How long does it take to hire a data engineer? +
KORE1 puts an internal search at 6-10 weeks, followed by two to four months of ramp-up, so most companies wait five to seven months from the decision to reliable data.
### Can we build our own data team later if we start with a data partner? +
Yes. Your new hires start from documented metric definitions and data models, and you decide how much of the work the partner keeps.
### What does a data partner cost? +
It depends on how many tools your company runs on and how much ongoing help you need. Silicon gives a written scope and an exact quote after a short discovery.
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## Tell us where your data lives today.
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Talk to Sujay
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