About Tradeify
Tradeify is a fast-growing futures prop trading company. We run a performance-driven B2C growth engine across paid and organic channels and we are building additional products and sister brands. Our next phase requires a clean, trusted measurement layer so we can scale spend and channels with confidence.
Role Summary
We are hiring a hands-on Marketing Operations lead to own our tracking, marketing analytics, revenue modeling and reporting end-to-end. You will be the primary owner of the marketing data layer: from conversion tracking and tagging through to datasets and executive dashboards. You will unify performance data across paid, organic, referral, web analytics, and payment systems to produce channel-level ROI and revenue attribution we can trust. This role is high impact and will directly influence budget decisions, growth velocity, and channel allocation.
Key Responsibilities
- Own marketing measurement end-to-end, including defining and maintaining event taxonomy, UTMs, conversion definitions, and overall tagging/tracking hygiene via GTM (or equivalent).
- Manage and optimize analytics platforms such as GA4 (and its BigQuery data), Looker Studio, Hyros, Intercom, and additional measurement tools as needed.
- Implement and maintain conversion tracking across Google Ads and Meta Ads (including pixels, CAPI, deduplication, and diagnostics), and build high-quality audiences for activation and retargeting across Google, Meta, Bing, TikTok, and Twitter.
- Develop and maintain the marketing analytics foundation by modeling and preparing datasets directly in a data warehouse (BigQuery or similar), and reconciling data across GA4, Hyros, ad platforms, Intercom, and payment gateways to connect spend → conversions → revenue.
- Establish a single source of truth for core marketing KPIs (CAC, LTV, payback, ROI, funnel conversion rates) and analyze attribution models to evaluate channel performance across the full funnel.
- Build and maintain dashboards in Tableau or Power BI for ongoing performance monitoring, delivering clear, decision-ready insights across paid channels, SEO, lifecycle signals, and funnel health.
- Proactively identify anomalies, tracking breaks, and performance shifts ahead of stakeholder requests.
- Lead data quality, documentation, and governance, including automated checks for tracking integrity, documenting systems and definitions, and ensuring compliance with privacy and platform policies.
- Partner with stakeholders by translating data into actionable insights, clear narratives, and prioritized recommendations—communicating transparently, especially when performance or tracking issues arise.
Required experience and skills
- 4+ years in marketing operations, marketing analytics, growth analytics, or a similar role where you owned measurement end-to-end.
- Strong SQL skills with experience working directly in a data warehouse environment, ideally BigQuery.
- Hands-on experience with GA4, Google Tag Manager, and familiarity with analytics platforms such as Hyros or similar.
- Direct implementation experience with Google Ads conversion tracking and enhanced conversions, Meta Pixel and Meta Conversions API (including event deduplication), and audience creation and management across Google and Meta.
- Strong dashboarding experience in Tableau (preferred) or Power BI, with the ability to build dashboards independently rather than relying on BI teams.
- Demonstrated experience stitching marketing data to revenue data, including integrating payment gateway or processor data such as Stripe.
- Strong measurement rigor, including attribution fundamentals, channel-level ROI, funnel analytics, cohort analysis, and clear explanation of trade-offs.
- Operating style marked by proactive problem-solving, reliable communication, comfort with ambiguity, and the ability to thrive in a fast-paced startup environment.
Nice to have experience
- Intercom data extraction and analysis (or similar customer messaging/support platforms)
- Experience integrating additional sources (affiliate platforms, CRM/CDP tools, basic ETL connectors, platform APIs)
- dbt, lightweight data modeling discipline, or Python for analysis and automation
- Server-side GTM or broader server-side tracking approaches
- Experimentation measurement (A/B testing, holdouts, incrementality thinking)
- Experience in regulated categories (fintech, trading, gambling-adjacent policy environments)
Ways of working and engagement model
- Must have overlap with North American working hours and be available for recurring meetings as needed.
- Work is hands-on and execution-focused, including implementing tracking, building datasets in the warehouse, and delivering dashboards and monitoring.
- Early success (in the first 30–60 days) includes clean and validated Google and Meta conversion tracking, BigQuery or similar datasets that reconcile spend, conversions, and revenue, Tableau dashboards that support weekly decision-making, and documented definitions plus a prioritized list of measurement gaps to address next.