Nebius
AI cloud infrastructure
DataEngineeringTeamLead(AgenticSearch)
Neural analysis suggests this role is
optimal for Senior candidates.
“Data Engineering Team Lead (Agentic Search) at Nebius. Skills: Data Engineering, Data Modeling, Cloud Data Warehousing, Python, SQL, Snowflake, Airflow, DBT, Spark. Set engineering standards for code quality, testing, documentation, and on-call. Work closely with engineers across the company to make sure batch and streaming pipelines are done correctly”
What You'll Achieve.
Deliver trustworthy datasets for product & gtm analytics
Industry & Context.
Debugged them under pressure; Recovered from data incidents; Understand what it means to backfill a corrupted table
On-call
What They're Looking For.
Must Have
5+ years of Data Engineering experience, Designing and implementing scalable, analytics-ready data models, Designing and implementing cloud data warehouses, Hands-on experience with Snowflake (or a comparable cloud data warehouse), Grasp of data warehouse architecture, Deep knowledge of databases (schema design, query optimization), Familiarity with NoSQL use cases, Expertise in modern data orchestration and transformation frameworks, Solid understanding of cloud data services, Solid understanding of streaming platforms, Hands-on experience with the Spark / MapReduce paradigm, Understand when distributed processing is the right tool, Fluent in Python for production data work, Fluent in SQL for production data work, Operated data systems in production, Debugged data systems under pressure, Recovered from data incidents, Understand what it means to backfill a corrupted table, Authorized to work in the country in which they apply, Provide proof of employment eligibility as a condition of hire
Nice to Have
Preferably medallion schema, Kubernetes a plus
What You'll Do.
Set engineering standards for code quality
Work closely with engineers across the company to make sure batch and streaming pipelines are done correctly
Define and implement observability for the data platform: data quality checks
Partner with researchers
and product managers to deliver trustworthy datasets for product & gtm analytics
and relationships that model Tavily's search domain
Turn the mental model into a clean
Ensure the highest standards of data quality
and security across all environments
How You'll Work.
Team & Collaboration
Work closely with engineers across the company; Partner with researchers, engineers, analysts, finance, and product managers
Full Job Description
About Nebius: 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 set engineering standards for code quality, testing, documentation, and on-call Work closely with engineers across the company to make sure batch and streaming pipelines are done correctly Define and implement observability for the data platform: data quality checks, freshness monitors, lineage, schema evolution, and cost controls Partner with researchers, engineers , analysts, finance, and product managers to deliver trustworthy datasets for product & gtm analytics. Define the objects, entities, and relationships that model Tavily's search domain - agent inputs, URLs, chunks, agent sessions, crawls, and the connections between them - and turn that mental model into a clean, queryable data model that the rest of the company can reason about. Data Governance: Can ensure the highest standards of data quality, integrity, and security across all environments. You may be a good fit if you: 5+ years of Data Engineering experience, with a focus on designing and implementing scalable, analytics-ready data models and cloud data warehouses (e.g., BigQuery, Snowflake). Have hands-on experience with Snowflake (or a comparable cloud data warehouse) and a strong grasp of data warehouse architecture preferably medallion schema. Deep knowledge of databases (schema design, query optimization) and familiarity with NoSQL use cases. Expertise in modern data orchestration and transformation frameworks (e.g.,
Applying for this Data Engineering Team Lead (Agentic Search) role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
ANONYMOUS · UNFILTERED
What do employees actually say about Nebius?
Real rants from real employees. Read before you apply.