Sr. Data Engineer (Remote)

Role overview Architect, build, and operate a data platform that supports real-time and batch use across product, growth, analytics, AI, and data services. The platform processes billions of events each day, so this hands-on role combines large-scale engineering with responsibility for production reliability, data quality, security, and long-term technical direction.

Responsibilities - Design and lead development of data pipelines, streaming systems, and data lakes for high-volume workloads. - Build solutions for both real-time and batch processing, making considered choices around performance, cost, scale, and maintainability. - Improve data quality through sound ETL/ELT practices, testing, monitoring, and observability. - Own production systems, identify likely bottlenecks and failure modes, and maintain uptime and correctness. - Partner with infrastructure and engineering teams on secure, resilient data services, and work with analytics, data science, product, growth, and business teams to meet their needs. - Create reusable tools, frameworks, and datasets, mentor engineers, and help shape the platform roadmap, including build-versus-buy decisions.

Requirements - At least five years designing, operating, and owning production data systems, ideally in high-scale or data-intensive settings. - Expert SQL skills and hands-on experience with Spark, Kafka, or comparable modern data processing frameworks. - Experience running data infrastructure on AWS. - Experience with infrastructure-as-code tools such as Terraform. - Proficiency in a data engineering language such as Python, Scala, or Java; Python is preferred. - Ability to take ownership of complex systems and work across teams on reliability, quality, and technical direction.

Benefits and work setup The role is remote-first in a global organization. Listed offerings include company equity for full-time employees, individual bonuses, open paid time off, company holidays, wellness days, and a meeting-free workday each week.