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  • Fullstack Data Engineer
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    Fullstack Data Engineer

    Austin
    5 000 - 7 500 USDNet/month - B2B
    Type of work
    Full-time
    Experience
    Mid
    Employment Type
    B2B
    Operating mode
    Remote

    Tech stack

      Data modeling

      advanced

      SQL

      regular

      Python

      regular

      NoSQL

      regular

      Machine Learning

      regular

      Virtualization

      regular

      BI

      regular

      Docker

      nice to have

      C++

      nice to have

      TypeScript

      nice to have

    Job description

    Online interview

    Hi!

    We're glad you checked out our job posting.

    We are currently looking for a specialist for the position of Fullstack Data Engineer to join our team. Below, you will find all the necessary information :)


    Localization: 100% Remote (Austin, Texas)

    Salary: $5000 - $7500 (B2B)


    Who are we?

    We are a rapidly growing American startup developing a dedicated tool for graphic designers that enables full-scale collaboration. You can think of it as a combination of Google Docs, Photoshop, and Miro – all in one place.


    In a world with an ever-growing appetite for content, especially in creative fields like video games, the pace of production, remote work, and talent management have become significant challenges. We decided to tackle these challenges by creating an innovative solution. We put collaboration at the heart of the creative process, providing teams with essential tools that significantly enhance content creation efficiency.


    Imagine drawings, graphic elements, animations, 3D tools, and videos—all fully accessible through a browser, for anyone, from anywhere :)


    Our continuous growth is reflected in our user base, which currently stands at 2,000,000 registered users and 70,000 active daily accounts. Our client portfolio includes companies such as Riot Games, Wooga, and Wildbrain. Among our individual paid subscribers, we have artists from top studios using our product, including Netflix and Disney Animation



    What You’ll do:

    Partner with the Product Team

    • Own the Product Analytics Plan: Develop and manage success metrics for features and releases, ensuring product decisions are data-driven.
    • Generate Deep Product Insights: Identify opportunities for new features or product improvements, spot potential issues and opportunities early, and inform execution and strategy.
    • Measure Feature Impact: Collaborate with the CPO and product designers to evaluate the success of each feature or release, maintaining a feedback loop for continuous improvement.
    • Establish Clear Dashboards & Weekly Reporting: Present a weekly “Weather Report” that gives the entire team a concise overview of key metrics, product usage trends, and actionable insights.


    Deeply Analyze User Retention & Conversion

    • Retention & Funnel Analysis: Investigate user engagement, identify friction points in the funnel, and pinpoint how to reduce churn and boost user activation.
    • Conversion Pipeline Optimization: Track and optimize the entire user journey, from discovery to premium upgrades, ensuring continuous growth in both free and paid segments.
    • Identify & Export PQLs: Leverage usage data to pinpoint product-qualified leads and export them via API to our CRM (Attio) to accelerate the sales pipeline.


    Develop Predictive Models & Recommendations

    • Algorithm Development: Design and implement recommendation strategies—ranging from heuristics to machine learning models—to personalize content for users.
    • Content & Interaction Classification: Build frameworks to classify user-generated content and interactions on the platform, laying the groundwork for more advanced analytics.
    • UGC Trend Discovery: Identify emerging trends in user-generated content, helping the team understand, leverage, and amplify new creative movements.
    • Data-Driven Growth: Use advanced analytics (e.g., user segmentation, A/B testing) to optimize engagement, retention, and revenue strategies.


    Design & Scale Data Infrastructure

    • End-to-End Data Pipelines: Plan, build, and maintain scalable ETL processes pulling data from various sources (APIs, databases, scraping).
    • Leverage the Modern Tech Stack: Work with MongoDB, PostgreSQL, Clickhouse, and Metabase. Integrate additional third-party tools with ETL processes.
    • Maintain & Expand Python Data Analysis: Oversee and improve our Python data analysis project that runs on a cron schedule to generate data for BI dashboards.
    • Maintain & Expand C++ Event Analysis: Oversee and improve our C++ interactive growth model project.
    • Contribute to TypeScript Analytics Code: Add and maintain Product Analytics code in our TypeScript projects, ensuring robust instrumentation and data integrity.
    • Enable Team-Wide Data Exploration: Create a culture of self-service analytics, giving every team member the tools and knowledge to explore data and derive insights for their own initiatives.
    • Bonus: Familiarity with Docker to containerize data pipelines and services for efficient deployment.


    Create Business Dashboards & Reporting

    • Executive & Internal Dashboards: Provide leadership with up-to-date analytics on key metrics, product performance, and business health.
    • Investor-Ready Reporting: Collaborate with finance and investor relations to prepare clean, concise data visualizations demonstrating traction and growth potential.


    Collaborate Across Teams

    • Reporting Structure: Report directly to our Chief Product Officer (CPO), providing actionable insights that inform product decisions and drive user acquisition, retention, and engagement.
    • Support GTM: Partner with the go-to-market team to deliver commercial insights, fueling client conversion and revenue growth.
    • Support CEO: Collaborate with the CEO to strategically present key metrics to current and prospective investors, propelling overall business expansion.


    Who We’re Looking For

    We won’t sugarcoat it: this role is demanding—but incredibly rewarding. If you love turning raw data into impactful insights, thrive on full-stack data responsibilities, and want to own your projects from concept to production, this role is for you. You should feel comfortable writing code daily, watching impact of latest feature releases, building ETL pipelines, diving deep into statistical analysis, and communicating with stakeholders in a fast-paced startup setting. When the opportunity arises, bring your business perspective and propose those $1M+ opportunities that propel product innovation and drive significant growth. In the future, this role can evolve in a more technical direction (e.g., greater focus on ML) or a more strategic one (e.g., Head of Data).


    Tech Stack

    • Databases: MongoDB, PostgreSQL, Clickhouse
    • Visualization & BI: Metabase, Posthog, Google Analytics
    • Languages:
    • Core analytics: Python/SQL
    • Supporting (nice-to-have or willing to learn): C++ and Typescript
    • Cloud Services: We tend to rely on self-hosted software but we do use cloud services when applicable.
    • Bonus: Docker for containerizing data science workflows



    What You’ll Need

    • Product Analytics Expertise: Proven ability to work closely with product managers to define success metrics, measure feature impact, and generate actionable insights.
    • User Retention & Conversion Analysis: Skilled at diagnosing churn, optimizing funnels, and boosting engagement.
    • Solid Data Engineering Foundations: Comfortable with data structures, modeling, and scalable ETL pipelines.
    • Databases & Querying: Proficiency in SQL (PostgreSQL, Clickhouse) and NoSQL (MongoDB).
    • Dashboard & Reporting Skills: Experience building executive-level dashboards and producing investor-ready data visualizations.
    • ML & Statistical Know-How: Familiarity with machine learning concepts, A/B testing, hypothesis testing, and user segmentation.
    • Technical Flexibility: Willingness to use any tool—including AI—to automate and deliver results quickly.
    • Fluent English: Clear written and spoken communication.
    • Availability: Daily standup meeting and other scrum rituals. Min 2h timezone overlap with both CET and CT timezones
    • Cooperation based on a B2B agreement and strong references from previous jobs.


    Nice to Have

    • Predictive Modeling: Hands-on experience with algorithms that drive recommendations or personalization.
    • A/B Testing & Growth: Familiarity with growth hacking principles and experimentation frameworks.
    • Data Governance & Security: Understanding of compliance, data privacy, and best practices.
    • Docker: Comfort with containerization for data science workflows.


    What You Get

    • In the future, this role can evolve in a more technical direction (e.g., greater focus on ML) or a more strategic one (e.g., Head of Data).
    • Competitive Salary: Based on experience and skillset.
    • Equity: Stock options that make you a co-owner in the company’s success.
    • Remote Flexibility: Work from anywhere, with annual global offsites and periodic regional gatherings.
    • Professional Growth: A chance to shape the future of art collaboration, driving product and strategy through data.
    • Dynamic Culture: Join an ambitious, diverse team committed to evolving how visual art is created and shared.
    • Unlimited Vacation
    • Unparalleled Work Flexibility
    • A fully paid company-wide global offsite once a year.
    • Regional offsite (Europe/US/Asia) every half a year.
    • Stock options that make you a co-owner in the company’s success.
    • An ambitious, diverse team committed to evolving how visual art is created and shared.


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    5 000 - 7 500 USD

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