Hire analytics engineers
who build a number you can trust.
A dedicated specialist, or a pod, who treats your tracking setup as infrastructure to be engineered and documented, not a snippet pasted in once and forgotten. Vetted on real implementations before they touch yours, working inside your GA4 property and tag manager, scaling monthly without a hiring cycle. You interview the engineer who'd actually own your tracking before anything is signed.
Interview before signing · First working session inside 14 days · Scale monthly
Tell us about the role
Start Your Enquiry
Send a short brief; an itemised proposal follows within 48 hours.
Hiring an analytics engineer through PixelCrayons gets you a vetted tracking and reporting-infrastructure specialist inside your team within 14 days. They build the measurement layer other teams build on: GA4 and Google Tag Manager configured properly, server-side tracking and consent mode implemented, an event taxonomy everyone actually uses, and dashboards that report the same number twice. It happens in your stack, with a named project manager and a weekly review in Prism behind them. You interview the engineer who would own your tracking first, resize the engagement monthly, and skip the full recruiting cycle along with the risk it carries. 21 yrs of delivery stand behind the bench.
Judge the record,
not the adjectives.
Outcomes tied to real engagements, not averages.
Rates for brands and companies buying for themselves.
Measurement skills,
built to be trusted.
Not the person who glances at a dashboard once a month. A specialist whose job is the pipe the dashboard runs through: what's tracked, what's validated, and whether two reports agree.
Tracking infrastructure
- GA4 property architecture and migrations off legacy setups
- Google Tag Manager and data-layer engineering
- Server-side tagging and conversion-API implementations
- Consent-mode and privacy-compliant tracking configuration
- Cross-domain and cross-device event stitching
Measurement & attribution
- Attribution-model configuration and validation, built and tested, not just switched on
- Event taxonomy design, so every team names the same action the same way
- Funnel and conversion-path instrumentation
- Tracking QA before launch, not after a dashboard shows a gap nobody can explain
- Data audits that separate what's broken from what just looks broken
Reporting infrastructure
- Dashboard builds in Looker Studio or the BI tool you already run
- Pipelines connecting ad platforms and CRM data into one source of truth
- Documentation written so a marketer can trust a number without pinging an engineer
- Handover-ready setup: a report someone else can maintain, not a black box
- Change logs for every tracking edit, so nobody inherits a mystery
Where an analytics engineer's week
actually goes.
The practical side of the role: the work itself, how to spot a good one, and what they need from you before they start.
A week inside the tracking plan
Most of the week is unglamorous, and that's the point. They compare what the tracking plan says should fire against what GTM preview mode and GA4 DebugView show actually firing, then chase the gaps. A developer renamed a button and a conversion event quietly stopped. A new landing page shipped without its data layer push. Consent mode is blocking a tag it shouldn't. Each fix gets a line in the change log and an update to the tracking plan. What time is left goes on reporting: a Looker Studio view rebuilt so two teams stop arguing about which number is right.
What to ask in the interview
Hand them a real problem: your paid-search conversions in GA4 don't match what Google Ads reports. A strong candidate asks questions before answering: which attribution model each side uses, whether consent mode is modelling conversions, whether the tag fires on a thank-you page that can be reloaded. A weak one names a tool. Ask how they'd name a new event and where that name gets written down. Ask what they check before publishing a GTM container version. If the answer includes preview mode, a workspace note and a rollback plan, you're talking to someone who has broken production tracking before and learned from it.
Have this ready before day one
Editor access to GA4, publish rights in Google Tag Manager, read access to the ad platforms and the CRM, and someone on the development side who can change the data layer. Without that last one, most fixes stall as a ticket in someone else's queue. Dig out whatever tracking plan exists, even a stale spreadsheet, and the list of reports people actually use to make decisions. Decide one thing up front: which system is the source of truth for revenue. If finance, marketing and sales each count a sale differently, the engineer can document all three, but someone on your side has to choose.
When this is the wrong hire
If what you need is someone to decide where next month's budget goes, you want a performance marketer who reads the numbers this role produces. If the problem is a warehouse of product data that needs modelling for a finance team, that's closer to data engineering, and the brief should say so. And if your tracking is broadly sound and the real gap is that nobody opens the dashboards, a new engineer won't fix a habit. This role earns its place when the numbers themselves are in doubt, or when a migration, a consent change or a new platform is about to put them there.
Brief to embedded,
in two weeks.
Brief & shortlist
You describe the stack, the gaps and what the numbers should answer; we propose the specialist, or pod, whose actual delivery history fits it. No generic CVs.
Interview them
You meet the real engineer who'd configure GA4 and the tag manager, not an account manager describing the setup secondhand. Ask about consent mode or tags; if the fit's wrong, we propose again.
Inside your stack
GA4, tag manager and CRM access granted, a tracking audit run against what's actually firing, your stand-ups joined. The first tracking working session is on the calendar within fourteen days of the NDA, not a quarter of onboarding later.
Scale either way
Add a second specialist when a migration or a new data source demands it; step down once the pipeline settles. Measurement capacity resizes monthly, with no headcount decision attached.
Requests, approvals and the weekly review for this engagement live in your Prism workspace. Each decision is recorded against the outcome it expected. See how Prism runs an engagement →
Meet the actual people before anything is signed
The person,
plus the system.
Hiring a specialist gets you their skills. A delivery organisation adds a structure around those skills, so your tracking stays maintained when someone is away or leaves.
Vetted on real implementations, not puzzles
Every specialist on the bench has built and validated live tracking before yours. Those builds were held to our own delivery standards before anyone joined a client's analytics stack. That work is reviewed weekly, held to the same documentation bar you'll see. Interview performance shows how someone explains an event taxonomy; a validated GA4 property shows whether it actually reconciles.
A second specialist briefed on the property from the start
A named project manager, a clear escalation path, and a named backup analytics engineer. Briefed on your engagement from day one, reading the tracking plan and tag documentation as the first one writes them. Leave or a departure? They take over tags and dashboards, no ramp-up. A solo freelancer has nobody to hand your tags to, and an in-house hire only gets that backup once a team exists around them. You get the specialist and the coverage that keeps the numbers trustworthy.
Team integration, not a portal
Your GA4 property, your tag manager, your Slack, your stand-ups. Dedicated means working inside your measurement setup and routines, not tracking requests lobbed into another team's queue.
Documentation you can hand to the next person
Every event documented with what fires it and why, every tracking edit logged, every audit of an inherited setup written up before anything changes. If the engagement ever ends, what's left behind is a measurement layer someone else can run, not a dashboard only one person understood.
How you typically hire,
versus through us.
An in-house hire earns its cost once your tracking and reporting needs are permanent and broad enough to keep one engineer fully occupied, and we'll say so plainly if that's where you are. Most measurement work starts smaller than that.
| Hiring it yourself | Through PixelCrayons | |
|---|---|---|
| Time to a working specialist | A full recruiting cycle: sourcing, interviews, notice periods, then a learning curve on your tracking setup | Inside 14 days of a signed NDA, interview included |
| Vetting | A resume and an interview; the gaps in a tracking setup surface once a report doesn't reconcile | Delivery history on real tracking implementations under our own standards, reviewed weekly |
| Management overhead | Yours entirely: recruiting, then double-checking every number before you trust it | A named PM and escalation path included; you direct what gets tracked, not the admin around it |
| Scaling | A new hiring cycle each direction: months up, severance down | Resize monthly: add a specialist ahead of a migration, step down after |
| Risk when it doesn't work | A mis-hire costs a quarter of decisions made on numbers nobody validated | Propose-again is built in; documentation means a handover costs days, not a rebuild |
Tracking verified before a single pound moved.
When a D2C fragrance retailer replatformed, the contract was zero data loss: every product, order and customer record inventoried and verified, and tracking confirmed working before marketing spend was ever allowed to scale. The full case study keeps the migration numbers and the timeline intact.
Read the case study →Frequently
asked.
A written proposal with roles, rates and availability arrives within 48 hours of the brief and the shortlist follows within days; you interview the specialist the same week, ask to see a real GA4 implementation they've built under NDA if you like, and the first working session inside your stack happens within 14 days of a signed NDA. Expect the first fortnight to prioritise a tracking audit: most GA4 properties have gaps or double-counting worth finding before any new dashboard gets built on top of them.
We audit first and say plainly which it is. Most engagements start as a fix: reconciling what's actually firing against what should be, closing gaps, deduplicating events, because a full rebuild on a working foundation wastes both budget and historical data. A rebuild is recommended only when the audit shows the existing setup can't be trusted incrementally, and we'll show you exactly what that audit found before recommending it.
NDA first, then GA4, tag manager and CRM access. A tracking audit follows, with a written summary of what they found. Once you agree the first month's priorities, changes start. They join your stand-ups from week one, so onboarding happens inside your process, not parallel to it.
Weekly, written: what was instrumented or fixed, what the audit turned up, and which numbers are now validated versus still under review. Dashboard changes are documented with what changed and why, so a report never quietly starts telling a different story than last month's. Agencies placing an analytics engineer on client accounts can have these reports in their own templates.
A single analytics engineer handles GA4, tag manager and dashboard work comfortably for most stacks. A second pair of hands joins when a major migration or a new data source genuinely justifies it, and the monthly resize runs both directions. We'd sooner start you with one engineer than sell a measurement pod you don't need yet. The proposal names the backup analytics engineer and says plainly whether their cover is part of the monthly rate.
Interview the person,
not the pitch deck.
Brief us on the stack and the gap, get a written proposal within 48 hours and a shortlist within days, and meet the actual specialist before anything is signed. If what you really need turns out to be an audit rather than an ongoing specialist, we'll say so on the first call.
Proposal in 48 hours · Interview before signing · Scale monthly
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