Data Engineer, Growth

Superhuman offers a dynamic hybrid working model for this role. This flexible approach gives team members the best of both worlds: plenty of focus time along with in-person collaboration that helps foster trust, innovation, and a strong team culture.

Preferred locations for team members for our Data Platform roles are our San Francisco or Seattle hubs.

Grammarly is now part of Superhuman, the AI productivity platform on a mission to unlock the superhuman potential in everyone. The Superhuman suite of apps and agents brings AI wherever people work, integrating with over 1 million applications and websites. The company's products include Grammarly's writing assistance, Docs’ collaborative workspace, Mail's inbox management, and Go, the proactive AI assistant that understands context and proactively delivers help. Founded in 2009, Superhuman empowers over 40 million people, 50,000 organizations, and 3,000 educational institutions worldwide to eliminate busywork and focus on what matters. Learn more at superhuman.com and about our values here.

As a Data Engineer on the RTM Growth team, you’ll own the pipelines, models, and datasets that power how Superhuman acquires and grows users across our multi-product, AI-native productivity platform: Grammarly’s writing assistance, Mail, Docs, Databases, and Go. You’ll partner closely with Growth, Performance Marketing, and Data Science to turn raw acquisition, ad-platform, and product-usage signals into reliable, decision-grade data.

Superhuman is a compound startup: we build many products as one integrated suite rather than standalone tools. That model creates an unusually rich data opportunity, with signals spanning paid acquisition, self-serve funnels, and cross-product usage for both consumers and enterprises. The data you model connects those surfaces, and the systems you build directly shape how efficiently we invest in growth and where our next wave of users comes from.

This is a high-ownership, high-impact role at the intersection of data engineering, machine learning, and growth. You’ll own growth-critical systems end-to-end, and your work will move the metrics the whole company watches.

What you’ll do

• 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.

• 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.

Nice to have

• 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.

Superhuman offers all team members competitive pay along with a benefits package encompassing the following and more:

• Excellent health care (including a wide range of medical, dental, vision, mental health, and fertility benefits)
• Disability and life insurance options
• 401(k) matching
• Paid parental leave
• 20 days of paid time off per year, 12 days of paid holidays per year, two floating holidays per year, and flexible sick time
• Generous stipends (including those for caregiving, pet care, wellness, your home office, and more)
• Annual professional development budget and opportunities

Superhuman takes a market-based approach to compensation, which means base pay may vary depending on your location. Our US locations are categorized into two compensation zones based on proximity to our hub locations.

Base pay may vary considerably depending on job-related knowledge, skills, and experience. The expected salary ranges for this position are outlined below by compensation zone and may be modified in the future.

US Zone 1

190,000 to 240,000

At Superhuman, we value our differences, and we encourage all to apply—especially those whose identities are traditionally underrepresented in tech organizations. We do not discriminate on the basis of race, religion, color, gender expression or identity, sexual orientation, ancestry, national origin, citizenship, age, marital status, veteran status, disability status, political belief, or any other characteristic protected by law. Superhuman is an equal opportunity employer and a participant in the US federal E-Verify program (US). We also abide by the Employment Equity Act (Canada).