Techesthete is an ad data engineering agency: pipelines, ad-platform integrations, and warehouses purpose-built for performance marketing and ad-tech teams.
Why generalist data engineering fails for ad data
Ad data is its own discipline. Attribution windows restate yesterday's numbers, every platform reports conversions differently, rate limits throttle the exact reports you need most, and a schema change in one API can silently corrupt a quarter of client dashboards. Generalist data teams treat these as edge cases; for an agency they are the daily workload. We build pipelines that expect them.
What an engagement covers
- Ingestion pipelines from Amazon Ads, SP-API, Meta, Google, TikTok, and retail media networks
- A modeled warehouse (dbt on Snowflake or BigQuery) where metrics mean the same thing everywhere
- Restatement-aware syncs that re-pull attribution windows instead of freezing stale numbers
- Client- and account-level reporting marts sized for multi-tenant agency use
- Monitoring that flags a broken feed before it reaches a client dashboard
- Documentation and handover so your team owns the stack, not us
How we work
Audit the current data flow account by account where numbers come from, where they break
Stand up ingestion for the highest-spend platforms first so value lands in weeks
Model metrics in dbt with tests, so ROAS in one dashboard equals ROAS in another
Layer on automation and alerting once the foundation is trusted
Typical stack
Frequently asked questions
An ad data engineering agency builds and operates the data infrastructure behind advertising: API integrations with ad platforms, ETL/ELT pipelines, a modeled data warehouse, and automated reporting. Unlike a media agency, it does not manage campaigns it builds the systems the campaign team relies on.
Ad data has quirks general pipelines mishandle: attribution windows that restate historical data, per-platform conversion definitions, aggressive API rate limits, and multi-account structures. Pipelines built for ad data re-pull restatement windows, normalize metric definitions across platforms, and are architected around those rate limits from day one.
Primarily US performance marketing, Amazon/retail-media, and ad-tech agencies including white-label arrangements where we operate as your engineering team. We also work with in-house teams running meaningful ad spend across multiple platforms.
A first working slice one or two platforms flowing into a modeled warehouse with live dashboards typically ships in 4–8 weeks. Full multi-platform coverage with automation and alerting is usually a 3–6 month build, shipped incrementally so reporting improves every sprint.