Data Engineer

Wynd Labs; New York (NY); Remoto; USD 140.000 - 190.000; Tempo pieno

Vantaggi offerti da questo lavoro

Equity package

Fully remote team

Descrizione del lavoro

Wynd Labs in the United States is seeking an experienced data engineer to build and optimize large-scale web data pipelines for AI model training. You will work on high-volume scraping, distributed processing, and analytics workloads, ensuring scalable, reliable data delivery across many workers and servers.

The role emphasizes Python, async programming, Docker & Kubernetes, and CI/CD for data workflows. You’ll contribute to platform APIs and data warehousing with modern cloud warehouses, in a

Competenze

• Bachelor’s degree or equivalent work experience.
• Strong Python (advanced) and async programming experience.
• Experience with high-volume web scraping and anti-bot evasion.
• Experience with distributed data pipelines and task queues (Celery, Kafka, RabbitMQ).
• Background in data warehousing and SQL (BigQuery/ClickHouse).
• Experience containerizing workloads with Docker and Kubernetes.
• Familiarity with CI/CD for data workflows (GitHub Actions, ArgoCD).
• Ability to design scalable APIs and data platforms.

Mansioni

• Maintain and optimize data pipelines for large-scale datasets.
• Support web scraping and data collection initiatives.
• Monitor data quality and troubleshoot pipeline issues.
• Document engineering decisions and pipeline workflows.
• Collaborate on R&D projects to improve data products.

Conoscenze

Python

Async programming

Web scraping

High-volume scraping

Distributed data pipelines

Task queues

Data warehousing

Databend

ClickHouse

BigQuery

Docker

Kubernetes

Helm charts

CI/CD

GitHub Actions

ArgoCD

Linux administration

Performance debugging

API design

Scalable APIs

Formazione

Bachelor’s degree or equivalent

Strumenti

Docker

Kubernetes

Helm

Descrizione del lavoro

Who We Are:

We build infrastructure that delivers massive amounts of web data to the companies training the world’s most powerful AI models.We're the team that helps to power and support Grass, a bandwidth-sharing network that lets us operate a massive distributed crawler, giving us unique access to high-quality public web data at global scale. On top of that, we’ve built pipelines for ingesting, segmenting, and annotating billions of videos, transcripts, and audio files, powering dataset creation for frontier labs.We’re lean, technical, and move fast. No red tape, no slow decision-making; just a team of builders pushing to expand what’s possible for open web data and AI.

Who You Are:

• Bachelor’s degree or equivalent work experiencePython (advanced)
• — strong grasp of async programming, multiprocessing, and writing production-grade code for long-running data jobsWeb scraping at scale
• — hands-on experience with high-volume scraping (proxies, rate limiting, anti-bot evasion). Experience with platform APIs and large media/metadata datasets (video platforms, social media)Distributed data pipelines
• — experience designing and operating pipelines across many workers/servers using task queues (Celery, Kafka, RabbitMQ, or similar)Data warehousing
• — practical experience with columnar/analytical warehouses; Databend, ClickHouse, or BigQuery strongly preferred; comfortable with complex analytical queries, partitioning strategies, cost-aware querying on cloud warehousesDocker & Kubernetes
• — containerizing workloads, writing Helm charts/manifests, managing deployments, autoscaling scraping/processing workloadsLinux & bare-metal ops
• — comfortable managing services on Linux servers, debugging performance issues (disk I/O, network, memory) without managed-cloud abstractionsCI/CD for data workflows (GitHub Actions, ArgoCD)Writing Scalable API

What You'll Be Doing:

Maintain, optimize, and troubleshoot database queries and related data systems to support efficient data access, processing, and reliability.Assist in creating, maintaining, and improving data pipelines used to collect, process, transform, validate, and deliver large-scale datasets.Support web scraping and data collection initiatives, including developing, testing, and maintaining scripts or tools used to gather publicly available data in accordance with Company requirements.Monitor and troubleshoot data pipeline issues, identify data quality concerns, and assist in implementing timely fixes to maintain data accuracy and operational continuity.Document engineering work, including database queries, pipeline processes, scraping workflows, technical decisions, issues encountered, and resolutions implemented.Participate in research and development projects to improve the Company’s data products and workflows.

Why Work With Us:

Opportunity. We are at the forefront of developing a web-scale crawler and knowledge graph that improves access to public web data and extends the value of AI to the people.Culture. We're a lean team with a high bar. We come to work not to be comfortable, but to find out what we're capable of and to do work that matters. We're not calling for people who keep things moving. We're calling for people who make everyone around them better.We prioritize low ego and high output. This is a fully remote team.Compensation. You’ll receive a competitive salary, benefits and equity package.