Lead Digital Marketing Manager

Decide where Ounass’s paid media money goes and prove what it returns. You own the cross-channel budget envelope, the allocation rules the channel leads execute against, the measurement standard that says which number decides, and the forecast. You run the incrementality programme and take over the marketing mix model. You also know how to setup and interpret marginal economics tactics on Performance Marketing Channels.

Every allocation decision you make can be defended with data in front of the VP Marketing and Finance, and the forecast you sign is the one the business plans on.

You report to the Director Marketing and sit beside the channel leads for Paid Search, Paid Social, Influencer Marketing, etc., who run their channels. You do not run campaigns. You set the envelope, the rules and the measurement; they own execution and pacing inside it. BI, Data, Growth, and Finance are your closest partners. Commercial and Retail Media are your main internal clients for the numbers

Own the paid media budget envelope across Paid Search, Paid Social, Display and programmatic, Affiliates and Influencer, by market (UAE, KSA, Kuwait, Qatar, Oman and Bahrain), against GMV, new-customer, CAC and efficiency targets.

Set the allocation rules and the marginal efficiency, growth, and CAC thresholds the channel leads trade against. Move money between channels and markets when the data says so, and write down why.

Run the reallocation cycle: a weekly pacing read, a monthly rebalance and a quarterly reset tied to the reforecast. Steer and optimise the budget control tower.

Separate brand-funded spend (Brand Exposure, booked through Retail Media) from Ounass-funded spend, so Net DM is reported cleanly with Finance.

Balance short-term efficiency against the planned shift of investment towards upper funnel. Show what the shift costs in blended efficiencies and when it pays back.

Define the measurement standard: which number decides a budget move, when platform attribution and last-click are overruled, and when a lift study or geo holdout is required before a channel scales.

Run the incrementality programme: geo holdout or lift studies per major channel, designed with BI, written up with the budget decision that followed.

Read and act upon the marketing mix model’s insights

Triangulate platform attribution, GA4, the app MMP (Adjust) and the mix model into one view. Publish diminishing-returns curves per channel and market.

Keep the tracking foundation sound with Tech and BI: server-side events, consent, app attribution (SKAdNetwork). A tracking error that corrupts a budget decision is a serious miss.

Own the paid media forecast (weekly, monthly, annual) by channel and market. Forecast accuracy is a tracked KPI for this role.

Build the paid media input to the annual budget and each reforecast, with scenarios Finance can use: what AED 5m more or less buys, and where.

Set the targets per channel and market with the channel leads and defend them in the planning cycle.

Own the performance story to the VP marketing and Finance: what moved, why, and what changes. One source of truth built with BI; no parallel decks.

Turn the numbers into decisions for Commercial and Retail Media: category and brand-level investment views, and readiness for private sales, Ramadan, Eid and peak.

Automate reporting, pacing alerts and allocation recommendations. Use AI tools daily in your own work and track the hours saved.

Govern platform automation: decide where it runs, what guardrails apply, and how it is measured against manual control.

Manage the measurement: the MMM, lift-studies, and the Marketing Platform’s measurement teams.

Protect the brand: reject placements or tactics that cheapen it, even when the CPA looks good.

Document the standards (allocation rules, test designs, forecast method) so the team runs the same way with or without you in the room.

8+ years’ experience in performance marketing, with ownership of a multi-channel paid media budget, in-house at a scaled e-commerce or consumer business.

Has designed and read incrementality tests (geo holdouts, conversion lift) and changed a budget decision because of them. Bring two from the last 12 months: what was tested, how it was measured, what was learned and what moved.

Has built, owned or used a marketing mix model and can say where it is wrong. Has owned a budget forecast and been held to its accuracy.

Proficiency in SQL and experiment statistics: sample size, power, significance, holdout design. You read raw data yourself. Python or R is an advantage.

Working fluency in GA4, an app MMP (Adjust or AppsFlyer, including SKAdNetwork) and a BI tool (Tableau or Looker). You notice when the data is wrong, and you keep digging until you know why.

Hands-on background on Google Ads and Meta at scale, and working knowledge of Snap and TikTok: enough to challenge a channel lead on set-up, bidding and attribution, without needing to run the account.

Multi-market allocation experience, ideally with an app component and a market the size of KSA in the mix.

Experience working cross-functionally with Finance, Commercial, BI and Data, and fluency in their language: margin, CAC, payback, CLV, contribution.

Clear writing and presenting: a one-page recommendation the Leadership can act on, and a weekly read the channel leads can act on.

Daily AI use in your own workflow, with examples of time saved.

Degree in marketing, economics, statistics or another quantitative field, or equivalent experience

Arabic, written and spoken, and experience reading KSA and UAE audiences.

Luxury, fashion or beauty e-commerce, ideally in the GCC.

Python or R; a modern data stack (dbt, Athena or BigQuery); Looker Studio or Tableau at builder level.

Has written decision documents in a culture that runs on them (Amazon-style narratives or similar).

Brand-funded, co-op or retail media exposure, including partner reporting