Data Engineer (Agentic Search)

Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.

Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.

Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.

• Contribute to the design, development, and operation of Tavily's data platform — from real-time ingestion through data warehouse medallion layers to consumer-facing datasets and dashboards.
• Build and maintain reliable batch and streaming pipelines that ingest data from production services and external systems.
• Design and evolve scalable, analytics-ready data models in the data warehouse.
• Work closely with engineers across the company to ensure data produced by production systems is reliable, well-structured, and usable downstream.
• Improve observability across the data platform, including data quality checks, freshness monitoring, lineage, schema evolution, and cost controls.
• Partner with researchers, engineers, analysts, finance, and product managers to deliver trustworthy datasets for product, search quality, ML, and GTM analytics.
• Contribute to defining the objects, entities, and relationships that represent Tavily's search domain — including agent inputs, URLs, chunks, agent sessions, crawls, and the connections between them — and translate them into clean, queryable data models.
• Improve engineering practices around testing, documentation, deployment, and incident response.
• Investigate and resolve production data issues, including broken pipelines, corrupted datasets, schema changes, and large-scale backfills.
• Contribute to technical standards and best practices for data engineering across the company.
• Help maintain high standards of data quality, integrity, security, and governance across environments.

• Have 5+ years of Data Engineering experience, with strong experience designing and implementing scalable, analytics-ready data models and cloud data warehouses such as Snowflake or BigQuery.
• Have hands-on experience with Snowflake, or a comparable cloud data warehouse, and a strong understanding of modern data warehouse architecture, preferably including medallion-style modeling.
• Have deep knowledge of databases, including schema design, query optimization, and familiarity with NoSQL use cases.
• Have strong experience with modern data orchestration and transformation frameworks such as Airflow and dbt.
• Understand cloud data services on AWS or GCP and have experience with streaming platforms such as Kafka or Pub/Sub.
• Have hands-on experience with Spark, MapReduce, or similar distributed processing systems, and understand when distributed processing is the right tool.
• Are fluent in Python and SQL for production data work.
• Have operated data systems in production: debugged them under pressure, recovered from data incidents, handled schema changes, and backfilled corrupted or incomplete datasets.
• Care deeply about data quality and about making datasets understandable and trustworthy for the people using them.
• Are comfortable working on ambiguous, cross-functional data problems and collaborating closely with both technical and non-technical stakeholders.

Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI 

Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.

Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. 

If you need accommodations during the application process, please let us know.