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Constructor is the next-generation platform for search and discovery in ecommerce, built to explicitly optimize for metrics like revenue, conversion r...
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Posted 4 days ago
Senior Data Engineer, Data Analytics
Agility Robotics
Remote
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Agility’s commercially deployed humanoids operate alongside teams in warehouses, manufacturing facilities, and distribution centers—tackling physicall...
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Posted 1 week ago
Principal Engineer, Data Platform
AlphaSense
Remote - United States
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AlphaSense is the AI platform redefining market intelligence and workflow orchestration, trusted by thousands of leading organizations to drive faster...
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Posted 1 week ago
Business Analytics Engineer, Customer Insights
Rad AI
United States - Remote
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At Rad AI, we’re on a mission to transform healthcare with artificial intelligence. Founded by a radiologist, our AI-driven solutions are revolutioniz...
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On this journey for over 12 years, Qventus is leading the transformation of healthcare. We enable hospitals to focus on what matters most: patient car...
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Warp: We're Building the Platform for Agentic Development Warp began with the vision of reimagining one of the fundamental dev tools, the terminal, to...
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Posted 1 week ago
Security Data Engineer
Anthropic
Remote-Friendly (Travel Required) | San Francisco, CA
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Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society...
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Posted 2 weeks ago
Member of Technical Staff, Data Infrastructure
Fireworks AI
San Mateo
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Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows,...
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Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are de...
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Eve is redefining legal technology for plaintiff law firms, and we're building the team that will take us there. We help firms handle more cases, reco...
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How it works
Post a job, read applications and hire in one place.
Career context
Every AI system starts with a data pipeline
Data engineers build and run the systems that move, clean and model data: ingestion, ETL and ELT pipelines, warehouses and lakehouses, streaming, and the quality checks that make analytics and machine learning trustworthy. AI has made the role more important, not less: models are only as good as the data that reaches them.
The roles below come from data infrastructure companies, AI labs and product teams. They range from analytics engineering (SQL, dbt, modelling for analysts) to platform work (Spark, Kafka, orchestration, cost and reliability at scale). Read each listing to see which side it leans to.
Why RemoteAI
Built for AI specialists.
Not general job boards.
Some roles are posted here by the company, others link to the company's own job page. Closed roles are marked as closed, and there are no recruiter markups.
AI-only job listings
Roles are filtered to AI work. Each listing shows the company and links to its own job page.
Direct access to hiring teams
No recruiter in the middle. Your application goes to the company making the decision, here or on its own job page. No markups.
Free for candidates
Your profile, browsing and up to 20 applications a day are free. No placement fee, no share of your salary, no exclusive contract.
Pay shown when known
Jobs posted on RemoteAI show a pay range. Listings from company career pages show it when the company publishes one.
Remote roles
Remote and remote-friendly roles. Some require timezone overlap or a country, and the listing says where you can work from.
Full application tracking
Track all your applications, messages, and interviews in one place. No more losing track of where you applied.
Step by step
How to find a data engineer job on RemoteAI
Each listing shows the range the employer published, when there is one.
Describe pipelines you own
Volume, sources, freshness, failure handling. "Ingests 2 TB/day from 40 sources with 15-minute freshness" says more than a tool list.
Show data quality habits
Tests, contracts, monitoring and alerting. Teams hire data engineers who prevent bad data, not only move it.
Apply on the employer's page
Each listing links to the official application. Mention the warehouse and orchestration tools you match.
Profile guide
How to stand out as a data engineer
Not all profiles get responses. These are the signals that separate candidates who get interviews from those who don't.
SQL and data modelling
Dimensional models, dbt, clear and fast SQL: the base of every data engineering interview.
Orchestration
Airflow, Dagster, Prefect: scheduling, retries, backfills and dependencies done right.
Streaming
Kafka, Flink or Spark Streaming experience is less common: show it if you have it.
Cloud warehouses
Snowflake, BigQuery, Databricks, Redshift, including cost control.
Data for ML
Feature pipelines, training datasets, embeddings and vector stores connect data engineering to AI teams.
Reliability
SLAs, lineage, incident handling. Pipelines that run quietly for months are the goal.
Explore more roles
Every AI specialty. One platform.
ML Engineer jobs
Production ML, deep learning & AI infrastructure
LLM Engineer jobs
RAG pipelines, agentic systems & generative AI
Data Scientist jobs
Analytics, forecasting & applied ML
MLOps Engineer jobs
ML infrastructure, model serving & CI/CD
NLP Engineer jobs
Language models, transformers & text AI
AI Product Manager jobs
AI-native product strategy & roadmap
Computer Vision Engineer jobs
Image AI, object detection & edge deployment
AI Automation Specialist jobs
AI agents, n8n & workflow automation
Prompt Engineer jobs
LLM evaluation, RAG & prompt optimization
AI Trainer jobs
AI tutoring, RLHF & red teaming
Data Annotation jobs
Labeling, rating, evaluation & transcription
AI Engineer jobs
Applied AI, LLM & generative AI products
Forward Deployed Engineer jobs
Ship AI solutions with customers
AI Safety & Governance jobs
Alignment, evaluations & responsible AI
Entry-Level AI jobs
Junior roles & AI internships
Freelance AI jobs
Contract & freelance AI projects
FAQ
Questions about remote data engineer jobs
Everything you need to know before applying for your first data engineer role.
A data engineer builds the systems that collect, move, clean and store data so analysts, products and machine learning models can use it: pipelines, warehouses, streaming and data quality checks.
Analytics engineers focus on modelling data inside the warehouse for analysis, mostly with SQL and dbt. Data engineers usually own ingestion, infrastructure and platform reliability. Many listings mix both.
SQL and Python first, then a cloud warehouse (Snowflake, BigQuery, Databricks), an orchestrator (Airflow, Dagster), dbt, and for platform roles Spark or Kafka.
Yes. AI teams depend on training data, feature pipelines and retrieval data. Data engineers who understand ML data needs move naturally into ML platform and AI infrastructure roles.
Yes, for normal use: profiles, browsing and up to 20 applications a day are free, with no cut of your salary. Credits are optional, for extra applications or to put one at the top.
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