Head Of Data Infrastructure & Analytics; Fully Remote

Head of Data Infrastructure & Analytics (Fully Remote)

Puffy City of Johannesburg, Gauteng, South Africa

Position :
Head of Data Infrastructure & Analytics

Compensation :
Up to USD $, per annum + up to 25% Performance Bonus (Equivalent in local currency, based on your location)

Total Annual Package :
Up to USD $

We're seeking a systems-obsessed data infrastructure leader to architect the analytics foundation that powers strategic decisions across our high-growth D2 C business.

This role is for builders who get more excited about preventing data disasters than presenting insights.

You’ll take the helm of our e-commerce data operations, leading a team that ensures data reliability drives confident decision-making.

Working closely with our Forbes Council Member CEO and cross‑functional teams, you’ll establish the gold standard for analytics operations while enabling data‑driven growth in a competitive global market.

• Build Systems That Matter, Not Presentations That Don’t
• Partner with the 1% Top 5 Mattress Brand in US
• Embrace Radical Flexibility
• Own the Technical Stack That Prevents Fires, Not Fights It

Data Quality Infrastructure (Your #1 Priority)

Audit existing tracking setup (GA4, GTM, Shopify, Klaviyo, ad platforms) and fix every configuration error

Build automated validation systems that catch bugs before humans see them

Implement pre‑leadership QA processes with hard gates (reports don’t go out until they pass)

Create monitoring and alerting – know within minutes when tracking breaks, not days later

Technical Architecture & Reliability Design and maintain server‑side tracking implementation for attribution accuracy

Architect data pipelines that handle $2 M+ monthly ad spend tracking without errors

Establish technical standards: "Here’s how we ALWAYS configure X" documentation

Operational Excellence Build the QA checklist: specific validation steps before any report reaches the CEO

Implement data observability: automated anomaly detection, metric health dashboards

Create runbooks: when X breaks, here’s exactly how to fix it in under 2 hours

Enforce zero‑tolerance culture: accuracy over speed, every time

Manage existing Analytics Manager + 2 Data Specialists with focus on quality over quantity

Train team on proper setup procedures and validation protocols

Say "no" to ad‑hoc requests that compromise data quality

Build scalable processes: solve problems once, systematically

Strategic Projects (Once Quality Is Bulletproof) Implement advanced attribution models for multi‑channel $24 M+ annual ad spend

Scale analytics infrastructure for international expansion

7+ years in digital analytics with proven track record of owning data quality in high‑stakes B2 C environments

Expert‑level knowledge: GA4, GTM, server‑side tracking, data pipeline architecture, e‑commerce tracking

Can diagnose and fix tracking setup errors across the entire stack – you don’t just identify problems, you solve them

Strong technical skills: SQL expert (can write complex queries in your sleep), Python or R proficiency for data validation

Data engineering knowledge:
Understand ETL / ELT, data warehousing, API integrations, event‑driven architecture

Experience building data quality systems:
Automated validation checks, data observability, monitoring frameworks

You’re a builder, not a presenter:
More excited about architecting systems than making slides

Zero‑bug mentality:
You take it personally when bad data gets through

Process‑driven:
You document, systematize, and scale solutions

Comfortable saying no:
Protect data quality even when it’s politically inconvenient

Firefighter turned fire‑preventer:
You’ve dealt with data disasters and built systems to prevent them

Proven team leadership:
Can manage 3+ person analytics team with focus on quality and growth

Can explain technical issues to non‑technical executives without dumbing it down or over‑complicating

Enforce standards:
Your team knows accuracy is non‑negotiable

Cross‑functional influence:
Work with engineering, marketing, and product to fix data at the source