Staff Software Engineer

Retail Media is no longer the "next big thing" — it's one of the fastest-growing, most competitive segments in digital advertising, and retailers are under real pressure to run it well. At retailmediatools, we build retail media infrastructure that lets big retailers plan, launch, and optimize retail media at scale. Every time a shopper opens a search page, a category page or an in-store screen, our Ad Service has a few milliseconds to filter, rank and return the right sponsored ads. Every impression, click, add-to-cart and order that follows flows back through our event pipeline into the attribution and reporting that advertisers pay on. We're a small, senior team of engineers and retail experts who ship fast and own what we build. Since joining ZetaDisplay Group, we've got the backing of a larger group behind us — without losing the lean, pragmatic way we've always worked. We're looking for an engineer who doesn't stop at a team boundary: someone equally at home in a Go service on the hot path, a dbt model in the warehouse and a Terraform plan for the cluster underneath both. If that sounds like you, read on. What you'll work on You'll work across three layers of one platform, not one team's slice of it. Go is our main backend language. Ad serving. The Go services behind our Ad Serving API: real-time filtering on keywords, categories, SKUs, stores and audiences, ranking on bid and relevance, budgets and serving status — running in multiple regions across the EU and US for enterprise retailers.Events, attribution and data products. High-volume tracking events streamed into BigQuery, dbt models that turn them into post-click, post-view and last-touch attribution, reporting, forecasting, bid suggestions and raw data exports — all with EU data residency and pseudonymized identifiers.Platform. GCP and Kubernetes, deployed with Flux (GitOps) and provisioned with Terraform, plus Postgres, Redis, Pub/Sub, Argo Workflows and the observability (Grafana, Sentry) that keeps it honest. Responsibilities Own significant parts of our ad-serving and event-tracking path end-to-end — from design through production, including a share of the on-call rotationShip changes that cross the stack in one go: a new targeting feature might touch a Go service, a dbt model, a Terraform module and a GitOps manifest, and you'll own all fourKeep the hot path fast and resilient — profile, cache, take hard dependencies off the request path, and catch latency and throughput regressions before our retailers doKeep the data correct and affordable: consistent event schemas and IDs between services and the warehouse, idempotent pipelines, clean backfills when something breaks, and BigQuery spend under controlRaise the bar on reliability: SLOs, alerting, load testing, incident follow-ups, and CI pipelines fast enough that people don't route around themHelp shape platform architecture decisions — multi-region rollout, storage choices, streaming vs. batch — not just execute themBe comfortable using modern AI-assisted engineering tools to move faster, and pushing past your core competencies when the team needs it Qualifications 8+ years in software engineering, with 3+ years building data-intensive or latency-sensitive systems in production — ad-tech, real-time bidding, search, recommendations, payments, trading or similarStrong, current experience with Go in production, or deep experience in another systems language (Java, Rust, C++) and a willingness to write Go every daySolid SQL and data modeling; hands-on with a columnar warehouse (BigQuery ideally) and event streaming (Pub/Sub, Kafka or similar)Real performance instincts: you think in p99s, and you've tuned Postgres queries, Redis usage, connection pools and gRPC under loadHands-on with Kubernetes, Terraform and GitOps (we use Flux) — you've debugged production resource, networking and rollout issues yourself, not just filed a ticketComfort working in a lean, senior team — you'll get autonomy fast, so experience owning systems (not just tickets) mattersStartup or scale-up experience — building things from a smaller, less-defined base — strongly preferred Nice to have Ad-tech domain knowledge: auctions and ranking, budget pacing, attribution models, IAB measurement standards, VASTdbt and analytics engineering; GCP specifics like the BigQuery Storage Write API, Datastream and Cloud SQLPrivacy-conscious data engineering: GDPR, pseudonymized identifiers, EU data residencySearch and relevance: hybrid keyword and embedding searchExperience integrating AI tooling into the engineering workflow Benefits 💪 Real ownership — small team, clear scope, no committee decisions🧭 Clear product focus, now with the resourcing of a larger group behind it🌎 Remote-first, flexible hours — we care about output😎 Meetings only when they earn their place on your calendar💸 Competitive compensation, benchmarked to reflect the seniority we're hiring for Our Mission 💫 We build the software that lets retailers create, manage, and run retail media that actually moves the needle for their brands. How to Apply Sound like a fit? Apply via LinkedIn with a short note on why you are a great fit. Bonus points if your note mentions a latency or data-correctness problem you tracked down and fixed.