About retailmediatools
retailmediatools builds retail media infrastructure that enables large retailers to plan, launch, and optimize retail media at scale. Its Ad Service filters, ranks, and returns sponsored ads, while its event pipeline supports attribution and reporting. The company is part of ZetaDisplay Group.
Responsibilities
•Own significant parts of the ad-serving and event-tracking path end-to-end, from design through production, including a share of the on-call rotation
•Ship cross-stack changes spanning Go services, dbt models, Terraform modules, and GitOps manifests
•Keep the hot path fast and resilient by profiling, caching, removing hard dependencies from the request path, and catching latency and throughput regressions
•Maintain accurate and affordable data through consistent event schemas and IDs, idempotent pipelines, clean backfills, and controlled BigQuery spending
•Improve reliability through SLOs, alerting, load testing, incident follow-ups, and fast CI pipelines
•Shape platform architecture decisions, including multi-region rollout, storage choices, and streaming versus batch
•Use modern AI-assisted engineering tools and work beyond core competencies when needed
Requirements
•8+ years in software engineering, including 3+ years building data-intensive or latency-sensitive production systems
•Strong, current production experience with Go, or deep experience with Java, Rust, or C++ and willingness to write Go daily
•Solid SQL and data modeling skills; hands-on experience with a columnar warehouse and event streaming
•Performance tuning experience, including p99s, Postgres queries, Redis usage, connection pools, and gRPC under load
•Hands-on experience with Kubernetes, Terraform, and GitOps, including independently debugging production resource, networking, and rollout issues
•Experience owning systems, not just tickets, and comfort working autonomously in a lean, senior team
Nice to have
•Startup or scale-up experience
•Ad-tech domain knowledge
•dbt and analytics engineering
•GCP services
•Privacy-conscious data engineering
•Search and relevance
•AI tooling integration
Conditions
•Remote-first with flexible hours
•Competitive compensation benchmarked to reflect the seniority being hired for
•Clear product focus and the resources of a larger group
•Small team, clear scope, and no committee decisions
•Meetings only when they add value
