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Superhuman Platform Inc
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. 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 .
As a Software Engineer on the Data Operations 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 strategic direction for the platform. 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, including ML research use cases. 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.
Ensure easy of use and cost effectiveness of company wide data infrastructure 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.
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