This is a hands-on engineering position focused on developing scalable data platforms, high-volume ingestion pipelines, and the foundational data systems that power analytics, product applications, AI workloads, and large-scale model execution. You will help architect our data lake, build reliable ingestion capabilities at scale, and shape the core infrastructure that supports the companys future growth.
This is an exciting opportunity to work with cutting-edge technologies and have a defining impact on the architecture and evolution of our data platform.
What Youll Do
Build complex, high-volume batch and near-real-time ingestion services while helping evolve the platforms streaming capabilities.
Design and implement data solutions for all application requirements in a distributed microservices environment
Develop and optimize large-scale data pipelines for batch and streaming use cases.
Ensure data quality, compliance, and governance.
Manage and optimize Kubernetes infrastructure, utilizing KEDA to dynamically scale resources for large-scale data processing workloads.
Own the full lifecycle of our data stack using Terraform and Kubernetes, from provisioning to application-level frameworks.
Provide technical guidance for the team, drive best practices around infrastructure, CI/CD, testing, and system design.
Deep-dive into memory management and performance tuning to ensure our large-scale distributed systems are both cost-effective and lightning-fast.
5+ years of experience as a Data Platform/Infra Engineer.
Proven track record of building and operating scalable data infrastructure specifically within Data Lake architectures.
Proven experience designing and operating large-scale data processing workloads on Kubernetes, including workload autoscaling with KEDA.
Strong proficiency in Python and SQL.
Hands-on experience with Infrastructure as Code, preferably Terraform.
Experience with managing a data orchestration platform such as Airflow or Prefect.
Experience with Snowflake.
