Job Description

Location: Remote

Department: Analytics Engineering

Reports To: Head of Analytics Engineering

Experience Required: 2 to 4 Years.

Possible Night Shift.

NOTE: Apply only if you have hands-on experience with the given tech stack mentioned in the Required Experience Section.

ABOUT THE ROLE

We're looking for a Senior Marketing Analyst to join our Analytics Engineering team and take ownership of marketing performance analysis across our client portfolio. This is a senior individual contributor role — you'll be handling complex, high-spend accounts independently, mentoring junior analysts, and serving as the go-to expert on marketing data and attribution for your clients.

You'll be replacing a senior team member, so we need someone who can hit the ground running — not someone learning the fundamentals on the job.

WHAT YOU'LL DO

Own end-to-end marketing analytics for multiple client accounts, from data validation to insight delivery
Analyze performance across all major ad platforms (Google Ads, Meta Ads, TikTok Ads, Snapchat Ads, Bing Ads) and translate spend data into actionable recommendations
Build and maintain attribution models to determine true channel performance and ROI
Work directly with GA4 (BigQuery export) to conduct deep-dive analysis — funnel analysis, user journeys, event-level investigation, cohort behavior
Manage and troubleshoot data from Adobe Analytics where applicable
Work with third-party attribution and analytics platforms including Northbeam and Triple Whale to validate and cross-check attribution data
Analyze Shopify data (orders, AOV, customer LTV, product performance) and reconcile it against marketing platform reporting
Work with Stripe payment data for revenue reconciliation and subscription/LTV analysis
Integrate and analyze CRM data (HubSpot, Salesforce, or client-specific CRMs) for full-funnel visibility
Identify data discrepancies across platforms (e.g., GA4 vs Shopify vs ad platform numbers) and determine root causes
Build dashboards and reports that clients actually use to make decisions
Conduct A/B test analysis — statistical significance, lift, segment-level breakdowns
Present findings and recommendations directly to clients in a clear, non-technical way
Mentor junior analysts on the team, review their work, and maintain quality standards
Proactively flag anomalies, risks, or opportunities in client marketing data before clients ask

WHAT YOU NEED Required Experience

2 to 4 years in marketing analytics, performance marketing analysis, or a closely related role
Proven track record of real, demonstrable marketing analysis projects — not just dashboard-building, actual analytical insight generation
Hands-on experience with GA4, including BigQuery export analysis (not just the native UI)
Experience with Adobe Analytics
Experience working with attribution platforms — Northbeam, Triple Whale, or similar (Rockerbox, AppsFlyer, Singular)
Experience analyzing Shopify data (orders, products, customer data)
Experience with Stripe or similar payment processor data
Experience integrating and analyzing data from CRMs (HubSpot, Salesforce, or similar)
Strong hands-on experience across major ad platforms: Google Ads, Meta Ads, TikTok Ads, Snapchat Ads, Bing Ads
Advanced SQL — comfortable writing complex queries independently, not just reading existing ones
Strong understanding of attribution modeling (first-touch, last-touch, multi-touch, data-driven)
Experience with BI tools — Power BI, Tableau, or Looker Studio
Experience with Python for data analysis (pandas)
Experience of data engineering projects like ETL, building and maintaining data pipelines
Experience with GCP, BigQuery and/or another cloud data warehouse

Strongly Preferred

Experience with Marketing Mix Modeling (MMM)
Experience with funnel and cohort analysis for e-commerce or subscription businesses
Experience managing or mentoring junior team members
Experience working in an agency environment with multiple concurrent client accounts
Experience with e-commerce/DTC or subscription/telehealth business models specifically

Soft Skills

Can independently own a client relationship — not just execute tasks handed down
Comfortable explaining complex data findings to non-technical stakeholders
Sharp eye for data discrepancies and root-cause investigation
Proactive — flags issues before being asked
Strong written and verbal communication for client-facing work

WHAT SUCCESS LOOKS LIKE IN THIS ROLE

Clients trust your numbers without needing to double-check them
You catch data quality issues before they become client-facing problems
Your attribution recommendations directly influence client budget decisions
Junior analysts on your accounts produce better work because of your mentorship
You can pick up a new client's data stack and be productive within days, not weeks

WHAT WE DON'T NEED

Someone who's only worked with platform-native dashboards (Meta Ads Manager, Google Ads UI) without deeper analysis
Someone whose attribution experience is limited to reading a report someone else built
Entry-level or junior analysts — this role requires independent ownership from day one