Growth-Driven Paid Media Specialist

Open Farm; Toronto; Híbrido; CAD 65 000 - 75 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Healthcare coverage

RRSP plans with company match

Pet-friendly office

Discounts on pet food and products

Wellness days and personal days

Volunteer days

Resumo da oferta

Open Farm is seeking a Digital Marketing Specialist to own day-to-day paid media across Meta, Google, and TikTok. You’ll work with Growth, Creative and Analytics to launch, manage, and optimize campaigns driving new customer growth with efficient CAC.

You will traffic creative assets weekly, ensure specs and brand guidelines, and optimize campaigns end to end while collaborating with analytics to improve attribution and performance.

Qualificações

• 2 to 4 years of hands-on paid media experience with direct platform execution.
• Experience with Meta ASC+ campaigns and a working knowledge of Meta and Google platforms.
• Experience trafficking creative and managing campaigns end to end.
• Strong ability to optimize toward CAC and new customer acquisition.

Responsabilidades

• Own end-to-end ad launch process across Meta, Google and TikTok.
• Traffic creative assets weekly and ensure brand guidelines are met.
• Manage bids, budgets and daily optimizations to drive new customer growth.
• Analyze performance and translate insights into briefs for the creative team.

Conhecimentos

Paid media

Meta Ads Manager

Google Ads

Campaign management

Analytics

Excel/Sheets

Formação académica

Relevant degree or experience

Ferramentas

Meta ASC+

Feed management tools

Descrição da oferta de emprego

Open Farm is seeking a Digital Marketing Specialist to own day-to-day paid media across Meta, Google, and TikTok. You’ll work with Growth, Creative and Analytics to launch, manage, and optimize campaigns driving new customer growth with efficient CAC.

You will traffic creative assets weekly, ensure specs and brand guidelines, and optimize campaigns end to end while collaborating with analytics to improve attribution and performance.