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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer, Growth - **Company:** Superhuman LLC - **Location:** San Francisco, CA, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Sql Data Warehouse, Google AdWords, Airflow, Data Analysis, Continuous Integration, Python (Programming Language), Machine Learning, Operational Databases, Standard Sql, Workflow Management Systems, Snowflake, Apache Spark, Git, Data Layers, Data Lakes, Data Management, Data Pipelines, Databricks - **Published:** August 31, 2026 - **Apply:** https://www.dice.com/job-detail/11c1a785-5431-4926-a84e-8be95fdf77b1 ## About the Role * You have 3+ years of experience building and operating production data pipelines and data platforms, ideally for growth, marketing, or experimentation use cases. * You're highly proficient in SQL and Python, with deep hands-on experience in Spark and a modern lakehouse or cloud data warehouse (Databricks, Delta Lake, dbt, Snowflake, or similar). * You've supported machine learning workflows end-to-end, building feature pipelines, serving training and inference datasets, and partnering with data scientists to move models into production. * You have strong data-modeling and warehouse-design skills and a rigorous approach to data quality and observability. * You have experience with workflow orchestration and CI/CD for data (for example, Databricks Workflows or Airflow, with Git-based deployment). * You're comfortable using AI-assisted development tools like Claude Code or Codex to move faster, and you have the judgment to validate and supervise their output. * You communicate clearly and collaborate well with partners across Growth, Marketing, and Data Science. * You care about business impact and enjoy turning ambiguous growth questions into reliable, scalable data products. * You're a self-starting problem-solver who thinks from first principles, manages priorities across multiple projects, and thrives in a fast-paced, results-driven environment., * Exposure to growth and performance-marketing domains, especially ad bidding, paid-acquisition optimization, and web or landing-page experimentation. * Comfortable working with marketing and ad-platform data (for example, Google Ads, Meta, or LinkedIn) and core attribution and measurement concepts. * A track record of building self-serve data products that other teams rely on. * Experience partnering with performance marketers or growth leaders as a strategic data partner. ## Description * Design, build, and own scalable data pipelines (Spark/Databricks) that power ad bidding and paid acquisition optimization across channels such as Google, Meta, and LinkedIn. * Build and maintain the feature and training datasets that machine learning models rely on for bid optimization, budget allocation, and audience targeting, and help productionize those models alongside Data Science. * Develop the measurement, attribution, and experimentation data layer behind web and landing-page optimization, so Growth can trust the numbers behind every test. * Model growth and marketing data into clean, well-documented, reusable tables that analysts and data scientists can self-serve from. * Own data quality, freshness, and reliability for growth-critical datasets, with automated checks, monitoring, and alerting. * Partner with Growth, Marketing, Analytics Engineering, and Data Science to translate business questions into robust data models and trustworthy metrics. * Continuously improve the performance, cost efficiency, and developer experience of our growth data platform. You'll do this alongside partners across Growth, Performance Marketing, Analytics Engineering, and Data Science. We think from first principles, challenging the familiar to reframe problems and reach sharper solutions, and win with grit, staying with the hardest problems through the messy middle. You'll have the freedom to own your systems and directly influence the roadmap, and the complexity of what you build will grow quickly as we scale. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [7 Most Popular Web Developer Jobs in Europe](https://www.wearedevelopers.com/magazine/163-7-most-popular-web-developer-jobs-in-europe)