1 day ago
Responsibilities
- Build a query engine supporting efficient relationship traversals for demanding workloads.
- Design and drive high-priority platform projects that improve value, resilience, and scalability across multiple teams.
- Lead and guide engineers through architectural platform decisions.
- Identify system risks and reliability trends and design solutions to address them.
- Provide input on engineering initiative prioritization and short- and long-term roadmaps.
- Collaborate with internal product teams on requirements and growth planning as they integrate with REDAPL.
Requirements
- Bachelor’s, master’s, or PhD in Computer Science, Engineering, or a related scientific field, or equivalent experience.
- Extensive experience working with multiple types of data stores.
- Several years of experience contributing to platform- or infrastructure-focused initiatives.
- Experience leading impactful technical initiatives where performance, cost efficiency, ease of use, and resilience or operability are critical concerns.
- Significant backend engineering experience building and operating distributed systems at high scale.
- Preferred experience with graph databases such as Neo4j, Memgraph, JanusGraph, ArangoDB, Amazon Neptune, or PuppyGraph.
- Preferred production-grade experience with Apache Iceberg.
- Preferred understanding of query planning or experience contributing to production-grade query engines or related projects such as Trino, Calcite, Substrait, or DataFusion.
Benefits
- Hybrid workplace with office culture focused on collaboration and work-life harmony.
- Competitive global benefits, varying by country and employment nature.
- Continuous professional development.
- Opportunity to build tools for software engineers, influence product direction, and work with knowledgeable teammates.
Tech Stack
Neo4j
Categories
BackendData Engineering
About Datadog
Datadog is the essential monitoring platform for cloud applications. We bring together data from servers, containers, databases, and third-party services to make your stack entirely observable. These capabilities help DevOps teams avoid downtime, resolve performance issues, and ensure customers are getting the best user experience.