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Key Responsibilities and Required Skills for Growth Engineer

💰 $110,000 - $180,000

EngineeringMarketingData ScienceProduct

🎯 Role Definition

A Growth Engineer is a unique and dynamic software engineer who is laser-focused on business growth. This is a hybrid role that blends the technical prowess of a full-stack developer with the data-driven, experimental mindset of a marketer and a data scientist. The primary objective is to rapidly ideate, build, and iterate on product features and initiatives that directly influence user acquisition, activation, retention, and revenue. They are the technical architects of the growth engine, using code to unlock new opportunities, optimize conversion funnels, and scale what works. This role operates in fast-paced, cross-functional teams and is defined by a relentless pursuit of measurable impact on key performance indicators.

📈 Career Progression

Typical Career Path

Entry Point From:

  • Software Engineer (Full-Stack, Front-End, or Back-End)
  • Data Analyst / Business Intelligence Analyst
  • Marketing Technologist or Technical Marketer

Advancement To:

  • Senior or Staff Growth Engineer
  • Growth Product Manager
  • Head of Growth / Director of Growth Engineering

Lateral Moves:

  • Product Manager
  • Data Scientist
  • Senior Software Engineer (Product focused)

Core Responsibilities

Primary Functions

  • Design, develop, and deploy A/B tests, multivariate experiments, and personalization campaigns across the user journey to optimize conversion rates and user engagement.
  • Build and maintain the technical infrastructure required for rapid experimentation, including feature flagging systems, event tracking pipelines, and testing frameworks.
  • Collaborate closely with product managers, marketers, and designers to identify growth opportunities, formulate hypotheses, and translate them into actionable engineering projects.
  • Develop and implement user acquisition strategies by building landing pages, integrating with advertising platforms, and creating viral loops or referral systems.
  • Instrument and analyze user interaction data from various sources to gain deep insights into user behavior and identify friction points within the product.
  • Own the full-stack development of growth-related features, from back-end API integrations and database modifications to front-end UI/UX enhancements.
  • Optimize the user onboarding flow to improve activation rates, ensuring new users experience the product's core value as quickly as possible.
  • Develop and maintain the marketing technology (MarTech) stack, including integrations with CDPs (like Segment), analytics tools (like Amplitude), and marketing automation platforms.
  • Create and manage automated, triggered communication campaigns (email, push notifications, in-app messages) to drive user retention and re-engagement.
  • Build internal tools and dashboards to empower the marketing and product teams with self-serve analytics and insights into experiment performance.
  • Work to improve website and application performance, as page speed and user experience are critical components of conversion and retention.
  • Conduct deep-dive analyses on experiment results, presenting findings and strategic recommendations to stakeholders across the organization.
  • Implement and manage server-side tracking and event instrumentation to ensure data accuracy and completeness for growth analysis.
  • Build and maintain data pipelines that transform and aggregate user data, making it accessible for a variety of growth initiatives.
  • Rapidly prototype and launch Minimum Viable Products (MVPs) to test new growth channels, product ideas, or business models with minimal initial investment.
  • Enhance and scale referral programs and other viral mechanics by building robust tracking, attribution, and reward distribution systems.

Secondary Functions

  • Support ad-hoc data requests and exploratory data analysis to answer pressing business questions from leadership and other teams.
  • Contribute to the organization's data strategy and roadmap by advocating for better data governance, quality, and tooling.
  • Collaborate with business units to translate data needs and high-level growth ideas into specific, well-defined engineering requirements.
  • Participate in sprint planning, daily stand-ups, and retrospective agile ceremonies within the engineering and growth teams.
  • Mentor junior engineers or other team members on best practices for experimentation, data analysis, and growth-oriented development.
  • Stay current with the latest trends, technologies, and best practices in the growth hacking and digital marketing landscape.

Required Skills & Competencies

Hard Skills (Technical)

  • Full-Stack Development: High proficiency in at least one back-end language (e.g., Python, Node.js, Ruby, Go) and one front-end framework (e.g., React, Vue.js, Angular).
  • SQL & Databases: Advanced SQL skills for complex querying and data manipulation, with experience in both relational (e.g., PostgreSQL) and non-relational databases.
  • A/B Testing & Experimentation: Hands-on experience with experimentation platforms (e.g., Optimizely, VWO, LaunchDarkly) or building in-house testing frameworks.
  • Data Analysis & Visualization: Ability to analyze large datasets and visualize results using tools like Amplitude, Mixpanel, Tableau, Looker, or Python/R libraries.
  • Web Analytics & Instrumentation: Deep understanding of event-based analytics, tracking implementation, and tag management systems (e.g., Google Tag Manager).
  • MarTech & API Integration: Experience integrating and working with third-party APIs from marketing, sales, and data platforms (e.g., HubSpot, Salesforce, Segment, Stripe).
  • Data Warehousing & ETL: Familiarity with data warehouse technologies (e.g., BigQuery, Redshift, Snowflake) and building ETL/ELT pipelines.

Soft Skills

  • Data-Driven Mindset: A natural inclination to base decisions on data and evidence rather than intuition alone; obsessed with metrics and measurement.
  • Strong Problem-Solving: The ability to break down complex, ambiguous problems into manageable, testable components.
  • User Empathy: A genuine curiosity and focus on understanding the user's perspective, motivations, and pain points.
  • High Agency & Bias for Action: A proactive, self-starting attitude with a strong sense of ownership and an urgency to execute and deliver results.
  • Creativity & Curiosity: A drive to think outside the box, challenge assumptions, and constantly ask "what if?" to uncover new growth levers.
  • Collaboration & Communication: Excellent ability to communicate complex technical ideas to non-technical stakeholders and work effectively within a cross-functional team.

Education & Experience

Educational Background

Minimum Education:

  • A Bachelor's degree in a quantitative or technical field.

Preferred Education:

  • A Master's degree is a plus but not required; practical experience is valued more highly.

Relevant Fields of Study:

  • Computer Science
  • Engineering
  • Statistics
  • Data Science
  • Mathematics

Experience Requirements

Typical Experience Range:

  • 3-7 years of professional software engineering or data analysis experience.

Preferred:

  • Proven experience working within a dedicated growth team or on growth-focused projects in a B2C or SaaS company. A track record of shipping experiments and features that have measurably impacted key business metrics is highly desirable. Experience in a fast-paced startup environment is a significant advantage.
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