You'll join a central analytics team that supports product units across the company with their data needs. Rather than serving a single product, we build data systems that work across product teams — machine learning models, AI systems, and visualizations built on top of a wide range of product data sources. A big part of our mission is enabling self-service analytics, and that only works on a strong, reliable data foundation. That foundation is what our data engineers build. We already have data engineers on the team, and we're growing to keep pace with the demand for well-modeled, well-governed data across the organization.
What you'll do
Build the infrastructure and tooling required for optimal extraction, transformation and loading of data from a wide variety of data sources using cloud native big data services from AWS/Azure
Build and maintain the data pipelines that feed our AI systems, including retrieval and knowledge pipelines used by AI agents and RAG applications
Help design and maintain our data and knowledge architecture, including data and knowledge cataloging that makes sources discoverable and usable across AI pipelines
Maintain and operate our Azure infrastructure — provisioning and setting up the right resources, keeping environments healthy, and driving cost optimization and right-sizing (a solid DevOps foundation matters here)
Deploy analytics tools that utilize the data pipeline to provide actionable insights into customer usage, operational efficiency and other analytical and business performance metrics
Work with stakeholders including business analysts and data scientists to assist with data-related technical issues, support their data (infrastructure) needs, and prepare data for modeling and analytics
Support effective, data-driven decision making across stakeholders
What you'll need
Proven experience building and optimizing big data pipelines and architectures on large datasets (tens to hundreds of TB scale), including for AI/ML applications
Working knowledge of stream & batch processing into highly scalable data/metrics stores
Advanced SQL and hands-on experience with relational & non-relational databases like Postgres, Redshift, Cassandra, Data Explorer, etc.
Strong programming skills — Python is a must, Spark a plus
DevOps skills for cloud infrastructure — provisioning resources, infrastructure-as-code, monitoring, and cost optimization (Azure preferred)
Experience with data and knowledge cataloging or data governance tooling is good to have
Experience building big data consumption patterns such as data APIs and visualization platforms is good to have
Degree in Computer Science, Data Science, Data Engineering, or related; a Master's is a plus
