Hire Data Engineer for Marketing Agencies
Senior, direct, no layers

Most marketing agencies businesses do not need more dashboards. They need the unglamorous work underneath: data pulled from each source on a schedule, checked for errors, modelled into consistent definitions, and delivered to one reporting layer the team can trust.

The shape of the data decides the shape of the build. The agency runs on retainers and results: campaigns launched, creative approved, budgets paced, and clients who renew only when the pipeline proves the spend. Sources, models, and dashboards follow from that, not from a standard template, which is why two businesses in the same industry still end up with different pipelines.

Handover is part of the deliverable: documented models, scheduled pipelines the team can monitor, and dashboards the team can extend. The business should not need the person who built it to keep the numbers flowing.

The warehouse draws on CRM pipeline data, time-tracking records, client billing data, ad-platform spend and results, and analytics sessions and conversions. Each source is pulled on a schedule, checked for duplicates and missing records, and modelled into tables the business can query, so pipeline and revenue by client and channel, spend pacing against budgets, and creative approval cycle times all read from the same definitions instead of separate extracts.

The existing stack here usually means ad platforms (campaigns), analytics (performance), project tools (delivery and approvals), CRM (pipeline and clients), and reporting tools (client dashboards). Each of those systems holds part of the picture. The build connects them into one modelled layer, so a report draws from the warehouse rather than from five separate exports.

A sensible first project is one pipeline done properly, often CRM pipeline data feeding pipeline and revenue by client and channel, with the team using the resulting report for real decisions before anything else is added. A pipeline that proves itself on one decision earns the trust to carry the rest.

Take CRM pipeline data. Today it probably arrives as an export someone cleans by hand. In the pipeline it is pulled on a schedule, checked for missing or duplicate records, and modelled into the same definitions every report uses, so pipeline and revenue by client and channel is a number the team trusts instead of a spreadsheet they debate.

ad platforms handles campaigns. analytics handles performance. project tools handles delivery and approvals. CRM handles pipeline and clients. reporting tools handles client dashboards.

What changes in practice is where numbers come from. When CRM pipeline data and time-tracking records flow through tested pipelines into one modelled layer, the team stops rebuilding reports and starts acting on them. The time saved is real, but the trust is the actual deliverable.

That also changes how the business argues: disagreements move from whose spreadsheet is right to what the number means and what to do about it, which is where a marketing agencies team's judgement actually adds value. Browse all hire engagements or discuss your data setup directly.