/ Data Engineer
Data Engineering · Pipelines + Attribution

Know exactly which channels drive your pipeline

Run by a senior Data Engineer on MarketerHire's AI Operating System. Built inside your stack and owned by you, not software you run yourself.

Start your trial See a sample plan
★★★★★ 4.8 / 5 across 7,000+ customers
Pipeline attribution · acme.com Live · refreshed 4m ago
Pipeline driven · last 90 days
Email lifecycle$1.4M
Organic + SEO$1.1M
Paid search$820K
Paid social$380K
Events$240K
Where the budget really goes
Modeled credit says:
Email lifecycle #1 Organic + SEO #2
Last-click sent the budget to paid social instead.
Connects every tool already in your stack
● The blind spot

Eight tools. No single source of truth

The board asks what's working. You export spreadsheets and guess, because nothing ties spend to the pipeline it creates.

01
Budget chases what looks good
Spend pours into channels that win the dashboard and never convert.
02
A day a week vanishes into reports
Your team stitches spreadsheets by hand instead of running campaigns.
03
Marketing never wins the eng backlog
The real fix waits behind the product roadmap, quarter after quarter.
Last-click report 3 tools disagree
You Which channel actually drove Q1 pipeline?
Ad platformPaid social won it, +$610K
CRMNo, it was paid search
ProductMost signups came from email
✕  No source agrees, so you allocate next quarter on a guess
● Why attribution breaks

Every platform claims the same revenue

Attribution is the hardest number in your stack to get right, and the easiest to get wrong. Four forces keep it broken.

Your platforms reportGoogle, Meta, and LinkedIn, added up
actual revenue
280%
What actually closedThe revenue that hit the bank
100%
Trust any one dashboard and you fund the same dollar three times
01
Platforms double-count
Each ad network takes full credit for a conversion the others also claim.
02
Last-click pays the closer
Branded search and demo forms bank the credit that demand creation earned.
03
The signal keeps vanishing
iOS, cookie loss, and consent walls blinded the pixels you used to trust.
04
B2B journeys run for months
Twenty touches across a quarter, credited to whatever was easiest to measure.
● The build

One engineer builds the layer underneath

A senior Data Engineer wires every tool into one warehouse, models what truly drives pipeline, and automates the reporting on top.

01 · Data Layer

Unify the warehouse you own

Pull every ad, CRM, product, and billing tool into one place you control.

Ad platformssynced
Your warehouseone source
CRM + productsynced
→
02 · Attribution Model

See what really converts

Trade last-click guesses for credit across every touch in the journey.

Last-clickPaid social
ModeledEmail lifecycle drove it
→
03 · Auto-Reporting

Wake up to live numbers

AI workflows rebuild the report before your first meeting, every morning.

Mon6:01a
Tue6:00a
Wed6:00a
Built by a Data Engineer, not guessed by a tool. A senior expert owns every number. AI only makes it faster.
● What ships

Two tracks, one dedicated expert

First the foundation gets built. Then it keeps running itself, inside the stack you already own.

● Build the foundation

Stand up the data

The layer your tools were never going to build on their own.

  • A warehouse you ownEvery channel unified in one place, not a vendor black box.
  • Multi-touch attributionCredit modeled across the full journey, not the last ad clicked.
  • 14+ native integrationsAd, CRM, product, and billing wired in from day one.
● Run the loop

Keep it building itself

The reporting and activation that runs once the foundation is live.

  • Live dashboardsCAC, LTV, ROAS, and pipeline, current to the hour.
  • Reverse ETLAudiences and scores pushed back into your ad platforms.
  • AI workflowsReporting, lead scoring, and research that run on their own.
● Proven outcomes

Spend traced, pipeline defended

What changes once every dollar moves to the channel that actually converts.

How pipeline per dollar compounds ILLUSTRATIVE
1007550250 Pipeline / $ Wasted spend M1M2M3M4M5M6
+56%
B2B SaaS
LTV:CAC ratio, after spend moved to what converts
+42%
Sales-tech SaaS
SQL growth YoY once attribution went live
+65%
Event-management SaaS
MQL rate on $4.5M quarterly pipeline
$12M
B2B consulting
Pipeline traced, 67% fewer funnel stages

Real outcomes from past MarketerHire engagements, anonymized. Results vary by brand, market, and starting point — never a guarantee of future performance.

B2B SaaS Fintech Sales tech Consulting
● The alternative

A hire takes months. A tool only displays

 
MarketerHire
In-house hire
BI tool
Monthly cost
One flat fee, tooling included
$120K+/yr fully loaded
License plus an analyst
Time to deploy
Days to deploy
4–6 month search
You still build the model
Builds your attribution
A senior engineer
If you can find one
It only displays numbers
Turnover risk
None on your account
Rare, and they get poached
Whoever knows the tool leaves
Who owns the data
Your warehouse and accounts
Yours
Yours
● How it works

Audit, build, automate

STEP 01

Audit

Give us stack access. We map every tool and channel, then hand you a written data and attribution plan. Yours to keep.

UNIFIED DATA TODAY0 / 8 tools
First 2 weeks
STEP 02

Build

We stand up the data layer, attribution, and dashboards inside your stack, every piece owned by you.

Live by week 3
STEP 03

Automate

AI workflows run the reporting on their own. You walk into the board meeting already knowing what works.

✓ Reporting on autopilotdaily
✓ Pipeline by channellive
Every week after
● Questions buyers ask on the call

Honest answers before you book

Is this just AI picking my numbers?

No. A senior Data Engineer builds your attribution and owns the output. AI only makes the work faster.

Why not just hire one?

A Data Engineer takes four to six months to find, if you can. They're rare and they get poached. This one is live in days.

Can't a BI tool do this?

A BI tool displays numbers. It doesn't model your funnel or wire your stack. A person does that work; the tool just shows the result.

Will it touch our data safely?

You keep every account and the warehouse throughout. MarketerHire works as a user, never an owner.

Is it worth the monthly price?

It costs less than a single in-house hire, goes live in days, and carries no ramp and no turnover. The tooling is included.

What is the two-week audit?

We map your stack and channels and deliver a written plan: the gaps, the build, the integration map. Yours to keep, refundable in full. Work begins after you sign off.

● Pricing

One engineer, one monthly price

No retainer games, no surprise scope. Everything it takes to trust your numbers, for a flat monthly rate.

Data Engineer + AI tooling
$10K / month
Expert talent and AI technology, in your stack
A dedicated senior engineer plus the tooling to wire, model, and automate your marketing data.
  • Dedicated senior Data Engineer
  • Unified data layer and funnel attribution
  • Real-time dashboards for every core metric
  • Every integration, plus write-back to ad platforms
  • Automation that owns your reporting, built for you
Start your trial

Starts with a 2-week refundable audit · Month-to-month after · Cancel anytime

● Your trial's first deliverable

See what your data has been hiding

Your trial opens with the plan above: every gap, the build, and the channels really driving pipeline. The teams that wire this now defend budget with a number, not a guess.

Data & Attribution Plan · acme.comSAMPLE
✕ 8 tools, none agree on pipeline
✕ Last-click hiding your best channel
↑ Attribution live by week 3
Start your trial
The first thing your trial delivers · Yours to keep