{"id":2145354,"url":"https://alion.io/job/terrific-product-engineer-monetization-commerce-data","title":"Product Engineer — Monetization & Commerce Data","company":{"id":4219,"name":"Terrific","domain":"terrific.com","url":"https://alion.io/company/terrific","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"B","score":75,"open_postings":6,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-10T05:45:15Z"}},"role":"Backend","role_family":"Backend","seniority":"senior","employment_type":"contractor","work_mode":"remote","remote_scope":"stated_regions","remote_scope_basis":"posting_text","remote_working_hours":{"label":"European time zones","utc_offset_min":0,"utc_offset_max":2},"hiring_geo_confidence":"explicit","locations":["London, United Kingdom"],"countries":["GB"],"hiring_countries":["DE","FR","GB","AT","BE","BG","HR","CZ","DK","FI","HU","IE","IT","NL","NO","PL","RO","ES","SE","CH","EE","GR","IS","LV","LI","LT","LU","MT","PT","SK","SI"],"hiring_countries_total":31,"salary":null,"salary_estimate":{"min_usd":89000,"max_usd":176000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":27},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"BigQuery","optional":false},{"name":"Go","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Node JS","optional":false},{"name":"SQL","optional":false},{"name":"TypeScript","optional":false},{"name":"JavaScript","optional":true}],"status":"live","first_seen_at":"2026-09-20T07:31:00Z","employer_posted_date":"2026-09-20","last_verified_at":"2026-10-11T20:18:13Z","board_verified":true,"closed_at":null,"days_open":21,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":21},"description":"Product Engineer - Monetization & Commerce Data\nEurope · Remote · Full-time Contract\nProduct & Engineering · Commerce Media · Data · AI\nStart date: November 2026\nSee data that should be worth money? Make it worth money.\nSee a number nobody can explain? Go find out why.\nAt Terrific, we're building the next generation of social commerce-helping brands and publishers turn content, creators, live experiences and AI into commerce they own.\nOur technology brings shoppable video, live shopping, interactive timelines, polls and product carousels directly onto a merchant's website or app.\nNow we're looking for a Product Engineer to turn what those experiences already know about a shopper into a monetization product-and to decide what that product should be.\nTHE OPPORTUNITY\nThis is not a role where you'll inherit a roadmap.\nYou'll write it.\nTerrific sits on something most advertising companies cannot get. On a single customer's domain we see the video someone watched, the poll they voted in, the product they tapped, the coupon they used, what went into the cart and what they actually bought-first-party, consented, tied to a real catalog and a real checkout.\nMost advertising systems have one half of that and model the other half.\nNobody has turned it into a product yet.\nThat's this role. You'll build the layer that lets a retailer sell advertising inside their own site to the brands they already stock, and lets a publisher prove what their audience is worth in transactions rather than impressions.\nThere is no ad server today. No auction. No campaign model. No advertiser interface. It is a blank page, and you get to decide what goes on it.\nWHAT YOU'LL BUILD\nFirst, the thing only we can build: measurement.\nImpression, view, engagement, product interaction, add to cart, checkout, purchase. Client-side and server-side. One canonical event model, identity resolution, consent, and reporting a brand manager can read without an analyst.\nThen the thing that makes money: on-site retail media. Sponsored placements on inventory we already control-timeline, shoppable video, live-sold to brands the retailer already stocks. No auction required. No ad server required.\nAfter that, connectivity. Campaign and audience APIs into external buying platforms, and eventually programmatic supply through Google Ad Manager and Prebid.\nWe expect to rent more of the advertising stack than we build. You'll help decide which parts.\nWHAT YOU'LL OWN\nWriting the spec. You get a problem and an account, not a ticket.\nDesigning the event model across every Terrific surface-video, live, timeline, polls, chat, cart, checkout.\nIdentity resolution and consent, built so our customers keep their data structurally and not only contractually.\nAttribution: connecting advertising exposure to transactions, and being able to defend the method to a customer in one sentence.\nReconciliation between third-party reporting and our own logs, which never match.\nThe advertiser-facing surface-campaign setup, pacing, delivery, reporting.\nSponsored placement delivery and ranking on Terrific inventory.\nBuild-versus-rent recommendations, including which providers you'd shortlist.\nInstrumenting what you ship and watching it get used.\nDeciding what not to build this year, and saying so out loud.\nYou won't be expected to know advertising technology on day one. You will be expected to form an opinion, test it cheaply, and change it when the evidence says so.\nWHO YOU ARE\nYou're an engineer who thinks in products.\nYou've shipped data systems that carried real volume, not prototypes. You're comfortable with Node.js and TypeScript, strong SQL, and event pipelines-BigQuery and Pub/Sub, or close enough that you'll be fluent in a week.\nYou know what's actually buildable, how long it will take, and when to simplify scope to get something real into production faster. That last part is the job, not a compromise.\nYou care about the product and not only the code-which means you'll push back when what you've been asked for doesn't make sense.\nYou can sit with a retailer's analytics lead, work out what they actually need to see, and go build it without a product manager in between.\nAnd you're honest about numbers. In advertising, almost everyone's numbers are slightly wrong and most people don't say so. We'd rather be the ones who can explain the difference.\nHOW YOU'LL USE AI\nTerrific is AI-native by default.\nWe don't treat AI as a separate initiative or an occasional productivity tool. We use it as part of how we investigate, build, document and improve our work.\nIn this role, you'll have the freedom to use AI to:\nPrototype a data model in an afternoon instead of a sprint.\nGenerate and test transformation and reconciliation logic.\nExplore a customer's catalog, feed or event stream quickly.\nDraft the specs and documentation you'd otherwise postpone.\nBuild internal tools that let commercial teams answer their own data questions.\nMonitor pipelines and catch discrepancies before a customer does.\nWe're interested in what you can build with AI-not whether you use a particular tool.\nUse it to move significantly faster. Don't outsource your judgment to it.\nWHAT WE'RE LOOKING FOR\nAt least five years building production data or backend systems.\nNode.js and TypeScript. Strong SQL.\nReal event-pipeline experience-BigQuery, Pub/Sub, or close equivalents.\nExperience owning something end to end: you decided what it should do, then built it.\nAbility to design a data model someone else can still understand a year later.\nClear written communication. You'll write specs other people build from.\nGood judgment about effort, risk and commercial value.\nComfort working independently within a distributed, international team.\nProfessional fluency in English.\nA strong advantage:\nYou've joined advertising exposure data to transaction data before.\nAttribution, identity resolution, clean rooms, or conversion APIs.\nRetail media, commerce media, or publisher monetization.\nAnalytics or reporting products used by non-technical customers.\nSpanish, Portuguese or French for our LATAM and EMEA accounts.\nYou do not need to have built an SSP, and you don't need ad-operations history. If you've built serious data products and you can hold a product argument, the advertising domain is learnable and we'll teach it.\nHOW WE HIRE\nNo take-home project. About four hours of your time in total.\nA call with the hiring manager. Thirty minutes.\nA pairing session in our actual codebase, with one of our engineers. One hour. Not a whiteboard, not an algorithm puzzle.\n A product judgment conversation. We give you a real scenario: a retailer with five million monthly sessions, a product catalog, purchase data, Terrific inventory and Google Ad Manager, who wants brands to buy sponsored placements and wants purchases attributed to the advertising. We want to hear what you'd build first, what you'd refuse to build in year one, and where you'd cut scope.\nA technical design conversation. One hour.\nWe'll tell you what we're assessing before each round, and we'll give you feedback either way.\nSUCCESS LOOKS LIKE\nIn your first months, you will:\nShip an event and identity layer that covers every Terrific surface.\nProduce the first attributed revenue number a customer actually trusts.\nPut a working sponsored-placement product in front of one retailer's brand partners.\nGive our commercial teams numbers they can sell on.\nRecommend what we build and what we rent-and be right often enough that we stop asking twice.\nLeave behind a data model the next three engineers don't want to replace.\nSuccess is not shipping every item on a roadmap.\nSuccess is a retailer being able to say \"advertising on my own site produced this much revenue\"-and prove it.\nWHY THIS ROLE IS DIFFERENT\nMost engineering roles in advertising begin with a ticket and end when the ticket is closed.\nThis one begins with a blank page.\nYou'll decide what the product is, not only how it gets implemented. You'll work directly with customers, with the people making commercial decisions, and inside a company that already has the data-just not yet the product.\nThe advertising industry spends enormous effort modeling what Terrific observes directly.\nYou'll be the one who turns the observation into revenue.\nREQUIRED\nBased in Europe, or within a compatible European time zone.\nAvailable for a full-time engagement.\nAble to work remotely with teammates and customers across global time zones.\nProfessional fluency in English.\nAt least five years of hands-on production engineering.\nExperience with event pipelines, data modeling and analytics infrastructure.\nTerrific operates as a global company, and English is our primary business language. 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