Hire backend developers
who design the data layer before they write to it.
A dedicated engineer, or a pod, whose job is what the interface never shows: the schema, the API contract, what happens when two systems disagree about the same record. Vetted against real production data layers before they ever touch yours, working inside your repo and your stand-ups, and scaling up or down monthly without a hiring cycle. You interview the engineer who'd actually design the schema before anything is signed.
Interview before signing · Scale monthly
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Hiring a backend developer through PixelCrayons gets you a vetted API and data-layer engineer inside your codebase. They design the schema, the API contract and the integration points before writing the endpoint, in whichever language your systems already run: Node, Python or PHP, matched to your stack rather than a preference, with authentication, caching and scalability treated as day-one decisions, not retrofits. Their migrations run through your CI, backed by a named coordinator and an escalation contact. You review their actual work and interview the actual person first, scale the engagement monthly, and skip a full recruiting cycle and its carrying risk. Engineering delivery since 2004 stands behind the bench.
Judge the record,
not the adjectives.
Outcomes tied to real engagements, not averages.
Rates for brands and companies buying for themselves.
Data-layer skills,
commercially wired.
Not a developer who happens to write endpoints. An engineer whose job is the system underneath: what it stores, what it exposes, and what breaks when two things try to change the same record at once.
Data and API architecture
- Database design across SQL and NoSQL: schema, indexing, normalisation and when to break the rules
- REST and GraphQL API design: contracts that survive a second consumer, not just the first one
- Authentication and authorisation: session, token and role-based patterns applied correctly
- Migrations that run against a live database without a maintenance window nobody agreed to
- Data modelling for systems that will outlive the developer who built them
Systems and integration
- Third-party API and webhook integration: payment, CRM, ERP and analytics systems talking reliably
- Caching and queueing for the work that shouldn't run synchronously
- Rate limiting, retries and idempotency (a retried request applies once): the failure modes that only show up under real load
- Working across Node.js, Python and PHP, matched to the language your systems already run
- Logging and observability that make a 3am incident a read, not a guess
The commercial layer
- Working inside an existing data layer without triggering an unnecessary rewrite
- Code review as a discipline, not a formality before merge
- Documentation of schema and API decisions, written for the next engineer
- Recommending a language specialist once the architecture calls for deep expertise
- Estimation and scope conversations without invented precision
Below the interface,
what the work really involves.
How the job runs week to week, how to test for it in an interview, and what to hand over first.
A week spent mostly on agreements
Much of a backend developer's week goes on agreements between systems rather than new endpoints. They review a proposed schema change against every consumer that reads that table. They write or update the API contract before the front end starts building against it. They trace a mismatch between your records and a payment provider's, and decide which system is the source of truth. They look at slow queries in the logs and add an index or a cache where the evidence supports it. Expect written decisions alongside the code, because the next engineer will need them.
What to probe in the interview
Give them a real scenario: two services update the same customer record at nearly the same moment. Ask what happens, and how they would stop it going wrong. Strong candidates ask about volume, about which system owns the record, and about what the business can tolerate. Ask how they would rename a column that live code depends on, and listen for a staged migration rather than a single risky switch. Ask how they version an API once a mobile app depends on it. Specific stories from systems they ran beat textbook definitions every time.
What to have ready on day one
Read access to production data or a realistic anonymised copy, because a schema only makes sense against the data inside it. A list of every system that reads from or writes to your database, including the ones everyone forgets: the reporting export, the nightly sync, the partner integration. Credentials for third-party sandboxes, such as payments or CRM. Any existing API documentation, however stale, and any data dictionary, even an old one. And a decision on who approves schema changes. Without that, the developer either waits for permission or changes things nobody agreed to, and neither ends well.
When a backend hire misses
Hiring a backend developer to fix a slow page goes wrong when the slowness is in the browser, not the server, so check where the time goes before you brief. Briefing them with a list of endpoints and no picture of the business rules produces an API that works for today's screen and fails the second consumer. Handing them a system with no owner for the data means every integration argument lands on them. And if you need a finished product more than a better data layer, a project team fits better than an embedded engineer.
Brief to embedded,
interview before signing.
Brief & shortlist
You describe the systems, the data and the gap; we propose the engineer, or pod, whose actual architecture history fits it. No generic CVs.
Interview them
You meet the real person who'd design the schema and review a real API or database decision from something they actually shipped. Push on their migration and versioning calls; if the fit isn't right, we propose another engineer.
Inside your systems
Repo, database and integration access granted, the existing schema and API contracts reviewed, your CI and stand-ups joined.
Scale either way
Add a second engineer when the integration backlog grows; step down when it doesn't. Resizing happens monthly, so integration capacity moves without a headcount decision.
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 an engineer gets you their skills. Hiring dedicated backend developers through a delivery organisation gets you their skills inside a structure that keeps working when life happens.
Vetted on real systems, not puzzles
Every engineer on the bench has designed and shipped schema and API work before yours. That work ran under our own review standards before joining a client engagement. Pull requests are reviewed weekly, held to the same bar you'll see. A whiteboard exercise shows how someone talks about normalisation; we'd rather see a schema they designed and ask how it fared when a second consumer arrived.
A second engineer who already knows the schema
You get a named coordinator, an escalation contact, and a second engineer named against your data layer. Briefed on your systems from day one, following the schema notes and API contracts the first one keeps. Leave or a departure means they step in without a ramp-up: things a lone freelancer can't offer and an in-house hire needs a whole team behind them to get. You get the engineer and the coverage that keeps the data layer moving.
Architecture decisions made before the language is
A schema or an API contract designed well travels between languages. One designed badly doesn't survive contact with a second consumer, whatever language it's written in. This role starts with the decision that actually determines whether the system holds up.
Quality governance you can audit
A weekly review in Prism, written up and tied to what shipped, pull requests reviewed against a documented standard, and integration and migration decisions logged before they run. Wondering what a month of backend work bought you? The review notes and the migration log answer before we do.
How you typically hire,
versus through us.
An in-house hire earns its cost once the data layer is large enough and central enough to keep one engineer fully occupied, and we'll say so plainly if that's where you are. Most integration backlogs start smaller than that.
| Hiring it yourself | Through PixelCrayons | |
|---|---|---|
| Time to a productive engineer | A full recruiting cycle: sourcing, technical screens, notice periods, ramp-up on your data model | Eligible engagements can typically start within two to three business days after scope, payment and required access are confirmed |
| Vetting | A system-design interview and a take-home API; real schema decisions show up months later | Architecture and API delivery history on real systems under our own review standards, checked weekly |
| Management overhead | Yours entirely: recruiting, then reviewing every schema decision against your data model | A named PM and escalation path included; you direct the architecture priorities, not the admin around them |
| Scaling | A new hiring cycle each direction: months up, severance and notice periods down | Resize monthly: add an engineer when integration work grows, step down when it doesn't |
| Risk when it doesn't work | A bad schema decision sits under production data until someone dares touch it | Propose-again is built in; leaving takes a handover call with the schema notes, not a negotiation |
Structure a system can actually work with.
A search-visibility engagement, shown here because it is the same discipline a data layer lives or dies by. A B2B SaaS site's ambiguous naming and unstructured content were defeating search engines the way inconsistent data defeats a downstream system; the fix was entity cleanup, clear schema and consistent structure, and organic traffic rose in the months that followed. Clean, well-defined structure is what a reliable API sits on top of: the same discipline this role starts from.
Read the case study →Our commitments
Each one says where it applies and links to its full terms.
14-Day Risk-Free Trial
For eligible managed specialists. Up to 14 calendar days or 80 logged working hours, whichever comes first. End within the trial and pay nothing for eligible trial hours. Continue beyond it and those hours are billed at the agreed rate. Unpaid trial work remains ours if you stop.
Eligible managed-specialist roles only, one trial per customer. Not offered for AI, chatbot, prompt, automation, API-integration or QA work. Brand and graphic designers, brand strategists, video editors, content writers, copywriters and content marketers start with a paid pilot.
Full termsTime-zone overlap
At least four hours a day inside your core working hours. Two hours plus a daily written handover for the US West Coast.
Managed specialists only; not a staffing promise for project teams.
Full termsClear IP & Ownership Terms
Your materials remain yours. Bespoke deliverable rights, licences and handover are agreed before work starts.
All engagements.
Full termsClear Delivery & Escalation Ownership
Know who coordinates your engagement, who owns the work and how to escalate an issue.
All engagements. Roles may be combined and vary with your engagement.
Full termsQuestions buyers ask before they commit
Why not just hire a freelancer?
A freelancer can be the right choice for a single, well-defined task. We are set up for work that needs an accountable team: a named coordinator, delivery reviewed by QA and a senior lead before release, and continuity arrangements written into the engagement. Confidentiality, ownership and escalation terms are agreed in writing before work starts.
How does time-zone overlap work?
Your engineers work at least four hours a day inside your core working hours. We set the window with you before the engagement starts and hold it for as long as the engagement runs. For the US West Coast the live overlap is two hours each morning, with a written handover at the end of every Indian day. We do not run night shifts: engineers who work nights leave quickly, and keeping the same people on your team matters more to us than a longer overlap.
Can we try you before we commit?
For eligible managed specialists, yes: up to 14 calendar days or 80 logged working hours, whichever comes first. End within the trial and pay nothing for eligible trial hours; continue beyond it and those hours are billed at the agreed rate, and unpaid trial work remains ours if you stop. For project work, and for roles outside the trial, we offer a paid pilot with its scope, acceptance criteria, duration and fee agreed before it starts.
What if we want to stop?
Cancellation, notice and any renewal terms are written into your proposal or statement of work before you accept it. If an engagement ends early, we hand over completed, paid-for work and list any unfinished work separately. For an eligible specialist trial, you can stop within the trial window and pay nothing for eligible trial hours.
How we handle claims, credentials and your data: group credentials, dated ratings, how case figures are signed off, client permissions and data handling.
Frequently
asked.
Once we have a complete brief, we confirm the date you will receive your proposal. The shortlist follows within days; you interview the engineer the same week (a real schema or API decision they shipped is there to review under NDA on request). Eligible engagements can typically start within two to three business days after scope, payment and required access are confirmed. If your data model has undocumented assumptions, and most do, expect the first week to prioritise reading it before writing to it.
This page covers the architecture and data-layer thinking generally; the engineer proposed to you is fluent in whichever language your systems already run: Node.js, Python or PHP. If you're choosing a language from scratch or need deep expertise in one of them specifically, our language-specific pages (Node.js, Python, PHP, Laravel, Django) are the more direct route, and we'll point you there.
NDA first, then repo and system access. They review the existing schema and API contracts and write up what they found. Once you agree the first sprint's priorities, they join your stand-ups and changes happen inside your process, not parallel to it.
A single backend developer covers most API and integration backlogs on their own. A second joins when scope genuinely justifies it, and the monthly resize runs both directions. We'd rather start with one engineer on your API backlog than sell you a pod your data layer doesn't need yet.
Say so, early. Proposing a different backend engineer is part of the model, not a favour you have to argue for. The replacement inherits the documentation the first engineer kept (schema notes, API decisions, open pull requests), so a switch costs days, not a restart. And if the conclusion is that you need a different shape of help entirely, a fixed-scope migration, not an ongoing developer, we'll route you there instead. Your proposal names the second backend engineer who would cover your schema and API work, and says whether that cover sits inside the monthly rate.
Interview the person,
not the pitch deck.
Brief us on the systems and the gap, get a shortlist within days, and meet the actual engineer before anything is signed. If what you really need turns out to be a project rather than a person, we'll say so on the first call.
Interview before signing · Scale monthly
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