Software Engineer, Data Engineering

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. Superhuman team members in this role must be based in San Francisco or Seattle.

About Superhuman 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, Coda’s collaborative workspaces, Mail’s inbox management, and Go, the proactive AI assistant that understands context and delivers help automatically. 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.

The Opportunity To achieve our ambitious goals, we’re looking for a Senior Engineer to join our Data Enablement team and help us build a world-class data platform. Superhuman success depends on its ability to efficiently ingest over 70 billion daily events while using our systems to improve our products. This role presents a unique opportunity to experience all aspects of building complex software systems, including contributing to the strategy, defining the architecture, and developing and shipping to production.

Superhuman's engineers and researchers have the freedom to innovate and uncover breakthroughs—and, in turn, influence the roadmap of our product suite. The complexity of our technical challenges is growing rapidly as we scale our interfaces, algorithms, and infrastructure. You can hear more from our team on our technical blog.

Overview As a Software Engineer on the Data Enablement team, you will shape the architecture and technical strategy of our data platform, ensuring scalability, security, and efficiency across data engineering systems. You will design and lead the implementation of robust, scalable, and reliable systems that handle large volumes of data, empowering both product features and data-driven decision-making across the company.

Your work will span areas such as real-time & ETL data pipelines, cloud infrastructure, data lakes, and back-end services.

This role requires you to collaborate with cross-functional teams, including back-end engineers, Analytics engineering, Data Science engineering, and machine learning teams, to drive initiatives that support various business outcomes. As a senior IC, you will also mentor engineers and help set the platform's strategic direction.

In This Role, You Will

• Architect and lead the development of large-scale systems for data pipelines, data lakes that handle billions of daily events.

• Design and implement solutions that ensure data is available, secure, and scalable across the platform, enabling real-time and batch processing.

• Make high-level architectural decisions about system design, technology choices, and platform evolution, ensuring scalability and long-term sustainability.

• Collaborate with key stakeholders, such as product teams, data engineers, back-end developers, and ML engineers, to build tools & frameworks that power analytics, product features, and data-driven workflows.

• Work with business stakeholders such as Analytics Engineering and Data Science teams to build high-impact data products enabling business-critical features, research, and experimentation with a focus on efficiency and alignment

• Collaborate with Leadership in devising the charter and technical roadmaps

• Mentor engineers across back-end infrastructure and data engineering disciplines, fostering a culture of collaboration and technical excellence.

Qualifications

• Brings at least 10 years of experience in large-scale distributed computing systems, with expertise in both data engineering and data modeling.

• Has 5+ years of experience managing live production environments, including high-load systems or data-intensive workflows with a focus on uptime and reliability.

• Expert in SQL and proficient in technologies like Spark, Kafka, Terraform, and in at least one programming language commonly used for data engineering (e.g., Python, Scala, or Java).

• Strong knowledge of ETL/ELT design patterns, orchestration tools (e.g., Airflow, dbt, Dagster), and data quality frameworks.

• Ability to design scalable, secure, and maintainable data models and architectures, and understanding of data governance, privacy regulations (GDPR/CCPA).

• Hands-on experience with modern data storage