Hiring Marketing Technology Engineers: The Complete Guide

# Marketing Technology Engineer

**Location:** San Francisco, CA (Hybrid) · **Employment Type:** Full-time · **Level:** Mid-Senior

## About [Company]

[Company] is a growth-stage company with 2 million customers and a sophisticated marketing operation. Our MarTech stack powers 50 million customer interactions monthly—emails, push notifications, in-app messages, and personalized experiences.

Marketing technology drives growth. When our systems work well, customers receive relevant, timely messages that help them succeed. When they don't, campaigns fail, data is inconsistent, and opportunities are lost.

**Why join [Company]?**

- Work on MarTech at scale—2M customers, 50M monthly interactions
- Direct impact on company growth metrics
- Solve real data and automation challenges
- Join a 4-person MarTech team within a 100-person engineering org
- Series B company with strong product-market fit
- Competitive compensation with meaningful equity

## The Role

We're looking for a Marketing Technology Engineer to help us optimize our marketing systems. You'll work on customer data infrastructure, marketing automation, attribution, and the integrations that power our growth engine.

MarTech engineering bridges engineering and marketing. You'll translate marketing requirements into technical systems, build reliable data pipelines, and ensure campaigns reach the right customers at the right time. You need to understand both sides.

The ideal candidate has experience with customer data platforms and marketing automation, and can work effectively with marketing teams who think in campaigns and segments, not APIs and schemas.

## What You'll Work On

### First 30 Days
- Onboard to our MarTech stack, customer data flows, and campaign systems
- Understand our marketing team's processes and pain points
- Ship your first improvement (integration fix, data pipeline, or automation)

### First 90 Days
- Own a MarTech system component (CDP, automation, or attribution)
- Contribute to data quality or campaign reliability improvements
- Build relationships with marketing team members
- Understand our customer lifecycle and key metrics

### First Year
- Lead MarTech initiatives that improve marketing effectiveness
- Architect improvements to our customer data infrastructure
- Develop new capabilities (personalization, advanced segmentation)
- Establish MarTech engineering best practices

## Objectives of This Role

- Improve marketing campaign reliability and deliverability
- Reduce time-to-segment for new audience definitions
- Ensure customer data consistency across platforms
- Build attribution that marketing trusts
- Scale MarTech infrastructure for 3x customer growth

## Responsibilities

**Customer Data (50%)**
- Build and maintain customer data infrastructure
- Implement identity resolution and profile unification
- Design segmentation and audience building
- Ensure data quality and consistency across platforms
- Handle privacy compliance (GDPR, CCPA) for marketing data

**Marketing Automation (30%)**
- Design marketing automation workflows and triggers
- Build integration with email, push, and messaging platforms
- Implement personalization and dynamic content
- Create A/B testing infrastructure for campaigns
- Monitor campaign health and deliverability

**Analytics & Attribution (20%)**
- Implement marketing attribution models
- Build marketing performance dashboards
- Create experimentation and measurement infrastructure
- Support marketing team with ad-hoc analysis
- Integrate marketing analytics with product analytics

## Required Skills and Qualifications

**Technical Skills**
- 4+ years of software engineering experience
- 2+ years in MarTech, growth engineering, or data engineering
- Customer data platform experience (Segment, mParticle, or similar)
- Marketing automation platform experience
- Strong SQL and data pipeline skills
- Integration experience with marketing tools
- Proficiency in Python, JavaScript, or similar languages

**Domain Knowledge**
- Understanding of marketing automation concepts
- Familiarity with email deliverability and messaging
- Experience with attribution and marketing measurement

**Soft Skills**
- Clear communication with non-technical marketing teams
- Ability to translate marketing requirements into technical specs
- Patience for iterative marketing use cases

## Preferred Skills and Qualifications

- Email deliverability and ESP experience
- CDP implementation experience (Segment, mParticle)
- Personalization and recommendation experience
- Marketing attribution modeling experience
- A/B testing and experimentation background
- Privacy compliance experience (GDPR, CCPA)

## Tech Stack

**Customer Data:** Segment (CDP), custom identity resolution

**Marketing Platforms:** Braze (engagement), Marketo (B2B)

**Data:** Snowflake, dbt, Airflow

**Analytics:** Amplitude, Looker for marketing dashboards

**Infrastructure:** AWS, Kubernetes

## Compensation and Benefits

**Salary:** $130,000 - $175,000 (based on experience)

**Equity:** 0.03% - 0.10% (4-year vest, 1-year cliff)

**Benefits:**

*Health & Wellness*
- Medical, dental, and vision insurance (100% covered)
- $100/month wellness stipend
- Mental health support through Modern Health

*Time Off*
- Unlimited PTO with 15-day minimum encouraged
- 11 paid company holidays
- 16 weeks paid parental leave

*Professional Development*
- $2,000 annual learning budget
- MarTech and growth conferences
- Internal marketing and data training

*Financial*
- 401(k) with 4% company match
- Equity refresh grants annually

*Workspace*
- $1,500 home office setup allowance
- Hybrid work (2-3 days in SF office)
- MacBook Pro and equipment of choice

## Engineering Culture

**How we work:**
- Partnership with marketing—we're on the same team
- Data quality obsession—bad data breaks campaigns
- Reliability focus—campaigns must send on time
- Privacy-first approach to customer data
- Documentation for marketing team self-service

**What we value:**
- Marketing effectiveness over technical elegance
- Clear communication across technical and non-technical teams
- Customer experience through relevant, timely messaging
- Data privacy and responsible marketing
- Work-life balance (marketing emergencies are rare)

## Interview Process

Our interview process typically takes 2 weeks.

- **Step 1: Recruiter Screen** (30 min)
  Background discussion and role overview.

- **Step 2: Technical Screen** (60 min)
  Data engineering and MarTech fundamentals.

- **Step 3: MarTech Deep Dive** (75 min)
  Technical discussion about customer data, automation, and your experience.

- **Step 4: System Design** (60 min)
  Design a MarTech system component.

- **Step 5: Cross-Functional** (45 min)
  Discussion with marketing partner about collaboration.

- **Step 6: Team Interview** (30 min)
  Meet potential teammates.

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*[Company] is an equal opportunity employer.*