Nous Research
More roles at Nous ResearchData Engineer
Remote work allowed only within certain countries or regions.
North America
Employer listed it 11 days ago · Added 10 days ago
First listed 11 days ago and still open.
Salary
Not stated
Location
North America
Timezone
US East
Contract
Full-time
Experience
Mid
Category
Data
The employer did not publish a salary, and we have too few comparable roles to estimate one.
What the advert says
Quoted word for word from the employer's advert. Where it says nothing, we say so.
- Working hours
Open to any time zone with meaningful overlap with US hours.
- Where you can work from
- Location eligibility not confirmed
- Contract
- Not mentioned in the advert
- Experience asked for
- Not mentioned in the advert
- Pay
- Not mentioned in the advert
Remote flexibility
Region Restricted
Remote work is allowed, but only for candidates based in North America.
What the employer says
- Source listing states candidate location: "Americas (US time zones), Remote"
What Nomaders makes of it
- Applications outside the listed area are usually rejected
- Timezone overlap with the listed area is often expected
The quotes above are the employer's own words; the reading is ours. Always check the original listing and employment terms before working from another country.
Before you apply
Experience: employer states
Written as a requirement
- “Production experience with at least one workflow orchestration system such as Airflow, Dagster, Prefect, or an in-house equivalent.”
Questions worth asking: Nomaders interpretation
- The advert does not say where you can be based. Ask which countries they can legally employ or contract you from.
- No pay is stated. Ask for the salary range before investing time in interviews.
- The advert does not say whether this is employment or a contractor arrangement. Ask, as it affects tax and benefits.
Produced automatically from this advert's text; not reviewed by a person. The employer's own page is the final word.
About the role
The role
Join Nous to build and own the data pipelines behind our analytics and model training. This role centers on long-horizon agentic data at scale, turning millions of multi-step, tool-conditioned interactions into reliable datasets the whole company can trust. Open to any time zone with meaningful overlap with US hours.
Responsibilities
Build, operate, and continuously improve the data pipelines that feed analytics and model training.
Deliver reliable internal analytics so teams across Nous can make decisions on their own data.
Wrangle long-horizon agentic data into structured, well-documented datasets ready for analysis and training.
Choose ETL/ELT approaches based on destination capabilities, reproducibility, latency, and cost, and explain the tradeoffs behind each choice.
Own pipeline operations in production, including failures, re-runs, and backfills, and debug issues across jobs, storage, permissions, and downstream consumers.
Design and evolve schemas, storage formats, and data models as needs change.
Build memory-efficient processing that scales, using streaming and partitioning, and recognize when a workload has outgrown a single machine.
Communicate clearly about data location, lineage, quality, limitations, and fitness for use to engineers and non-engineers alike.
Qualifications
4+ years of data engineering experience building and operating production data pipelines.
Strong fundamentals in SQL, data modeling, and practical schema design and evolution.
Deep understanding of storage formats and database types, and when each one fits.
A working model of the data stack: ingestion, storage, transformation, orchestration, cataloging, and serving, and where responsibilities belong in each layer.
Strong Python, plus solid shell skills for batch and storage operations.
Hands-on cloud experience with object storage, batch compute, and identity and access management.
Production experience with at least one workflow orchestration system such as Airflow, Dagster, Prefect, or an in-house equivalent.
An instinct for data quality: you ask "is the data good?" and not just "did the pipeline run?"
Extensive use of AI-assisted development tools, with disciplined review of what those tools produce.
Preferred
Experience working with agentic or LLM-generated data, including structured, multi-step, tool-conditioned interactions.
Experience building data pipelines for model training.
Requirements
- ·4+ years of data engineering experience building and operating production data pipelines.
- ·Strong fundamentals in SQL, data modeling, and practical schema design and evolution.
- ·Deep understanding of storage formats and database types, and when each one fits.
- ·A working model of the data stack: ingestion, storage, transformation, orchestration, cataloging, and serving, and where responsibilities belong in each layer.
- ·Strong Python, plus solid shell skills for batch and storage operations.
Benefits
No benefits package published with this listing. Ask about it at first interview.
How to apply
- 1Check the flexibility label above, region restricted, matches where you plan to live and work.
- 2Tailor your CV to the role at Nous Research, mentioning your remote working experience and working hours (US East).
- 3Apply directly on the employer's careers page using the button below. Nomaders never handles your application.
Found 11d ago. Last checked today. Always confirm the details on the original posting, salary and location can change after publication.
Listing sourced from Company boards.
Pay not stated · You'll be taken to the employer's careers page.