Builds infrastructure and tools for Ramp's Analytics and Machine Learning Platforms, supporting data science lifecycle. Partners with AI and ML engineers; requires Python, workflow orchestrators, cloud platforms, and SQL expertise.
Builds and maintains data connectors, pipelines, and normalization services to acquire and validate identity attributes from various sources for the Identity Trust Graph. Requires 4+ years in OOP languages, containerized cloud systems like GCP/Kubernetes, and data integration experience.
Build and maintain production data pipelines that prepare conversational, voice, and multimodal data for ML model training and evaluation. Partner closely with ML engineers to deliver high-quality, versioned datasets and infrastructure.
Own and extend customer data ingestion platform and large-scale pipelines powering AI workers. Build data lake, retrieval layer, and infrastructure for syncing, enriching, and querying customer data across CRMs and third-party systems.
Build and operate the identity data platform that ingests, transforms, and serves high-volume identity data to power all Lumos products. Own ingestion pipelines, service layers, APIs, and observability for correctness and reliability.
Leads design and implementation of scalable data pipelines using dbt, Airflow, and SQL. Mentors data engineers, optimizes AWS infrastructure with Terraform, and builds integrations with MySQL/SQL Server/OLAP for analytics. Requires strong SQL/Python and production pipeline expertise.