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Our feature store supports complex data pipelines, embedding storage, and feature discoverability in multi-region production environments. It integrates deeply with our training, experimentation, and model serving workflows, ensuring high availability, low-latency access, and traceable lineage for every feature used in the ML lifecycle.

We’re looking for a Senior Software Engineer to design and build the next generation of Datadog’s feature infrastructure. You will work at the intersection of data engineering, ML infrastructure, and distributed systems to deliver scalable, low-friction solutions used across teams.

At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them.

What You’ll Do:

• Design and build distributed feature pipelines that power both training and low-latency inference use cases.
• Implement feature versioning, cataloging, and access management capabilities, ensuring traceability and governance across teams.
• Drive the integration of embedding storage systems (e.g., DDVector) to support scalable training and real-time retrieval.
• Build tooling to surface feature metadata, dependencies, and usage analytics to empower discovery and reuse.
• Partner with training, serving, and registry teams to deliver seamless integration across the AI Platform lifecycle.
• Own the operational excellence of your systems through monitoring, performance optimization, and cost efficiency.

Who You Are:

• You have 6+ years of experience as a data or platform engineer, including designing large-scale distributed systems for ML or analytics workloads.
• You’ve built and operated data pipelines or storage systems with technologies like Kafka, Snowflake, ClickHouse, dbt, or similar.
• You are proficient in Python, Scala, Go, or Java, and have production experience working in cloud environments (e.g., AWS).
• You understand data model design and storage formats optimized for ML workflows (e.g., columnar formats, LSM trees).
• You value cross-functional collaboration and can work closely with applied scientists, backend engineers, and infra teams.
• Bonus: experience building or operating a feature store, embedding database, or metadata management platform.

Benefits and Growth:

• New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
• Continuous professional development, product training, and career pathing
• Intradepartmental mentor and buddy program for in-house networking
• An inclusive company culture, ability to join our Community Guilds (Datadog employee resource groups)
• Access to Inclusion Talks, our internal panel discussions
• Free, global mental health benefits for employees and dependents age 6+

Datadog (NASDAQ: DDOG) is a global SaaS business, delivering a rare combination of growth and profitability. We are on a mission to break down silos and solve complexity in the cloud age by enabling digital transformation, cloud migration, and infrastructure monitoring of our customers’ entire technology stacks.

Equal Opportunity at Datadog:

Datadog is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and other characteristics protected by law.