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Jobs · 100 data companies · refreshed every 6 hours

Data engineering jobs.

Roles fetched from the careers pages of companies that take data seriously. Each one read for the skills it asks, turned into a practice plan, and linked to the company's own apply page.

  • A plan with every job, not just a link.
  • Your readiness, drill by drill.
  • Nothing older than 14 days.
See the live rolesHow it works

Live roles · newest first

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Get the plan.

Data Engineer, Analytics Engineer, Data Platform and Data Architect roles. No relevance ranking.

Software Engineer - Data PlatformMid

Vercel · Remote - United States · Remote

Data modellingStreamingWarehousingAWSAzure6 d ago8+ yrs

Vercel · job-boards.greenhouse.io · checked today

Software Engineer - Data Platform

Remote - United StatesMid · Remote8+ yrsData Platformposted 6 d ago

Skills, with evidence

  • Data modelling
    Define and maintain guidelines for data ingestion, creation, enrichment, and storage, while overseeing data modeling, ETL processes, and data warehousing (ClickHouse, Tinybird, Snowflake) to achieve low-latency analytics and scalable storage.must have
  • Streaming
    Design and implement a next-generation data platform that supports diverse requirements, including batch and real-time integrations, advanced analytics, and multiple data types, leveraging Kafka, Kafka-based tooling, and additional streaming technologies to power real-time data movement and processing.must have
  • Warehousing
    Define and maintain guidelines for data ingestion, creation, enrichment, and storage, while overseeing data modeling, ETL processes, and data warehousing (ClickHouse, Tinybird, Snowflake) to achieve low-latency analytics and scalable storage.must have
  • AWS
    Proficiency in cloud platforms (AWS, GCP, or Azure) and associated big data services.must have · not practised here
  • Azure
    Proficiency in cloud platforms (AWS, GCP, or Azure) and associated big data services.must have · not practised here
  • GCP
    Proficiency in cloud platforms (AWS, GCP, or Azure) and associated big data services.must have · not practised here
  • Machine learning
    Collaborate with data scientists and machine learning teams to evolve infrastructure that supports advanced analytics and AI initiatives, serving as a key contributor to strategy, tooling, and platform enhancements for ML-related workloads.must have · not practised here
  • Data quality
    Strong background in data governance and security, and adept at ensuring compliance with regulatory standards and protecting sensitive information.must have
  • Governance & security
    <p>You'll lead from the front, writing production-grade code, setting high standards for design and data governance, and mentoring a team of engineers as the organization grows.not practised here
  • Failure handling
    <li>Partner with Security, Compliance, and Legal teams to ensure adherence to data protection standards, and champion high availability and fault tolerance through comprehensive monitoring, alerting, and incident response practices.</li>

Your plan

  1. SQL

    drills at the Mid level

  2. Modelling

    drills at the Mid level

  3. Pipelines

    drills at the Mid level

The full plan, drill by drill, is on the job page.

See the full planApply on job-boards.greenhouse.io

leaves in 7 dremoved the moment Vercel closes it

How it works

Fetch. Read. Plan.

Every six hours, for every company on the list.

1 · Fetch

From the company's own portal

Straight from each company's job-board API. Data engineering roles only, 14 days at most.

GET boards-api.greenhouse.io/v1/boards/airbnb/jobs → 163 postings · 1 data role · 0 new since 06:00

2 · Read

Skills, with the sentence they came from

Each posting is read once. A skill only counts if the posting says it.

Spark 0.92 "…optimise PySpark jobs processing 2 TB/day…" Airflow 0.81 "…own our Airflow DAGs end to end…" Scala 0.55 not practised here, shown anyway

3 · Plan

Built from what already exists here

Skills map to practice topics. Five drills each, at the level in the title.

Senior → Intermediate + Advanced SQL ×5 · Spark ×5 · Pipelines ×5 · Modelling ×3 + interview questions · ≈ 11 h

Kept honest

Before you
trust it.

How fresh are the jobs?

Every company is checked every six hours. A role is removed after 14 days, or the moment the company closes it, whichever comes first. A re-posted job keeps its original date.

Do I apply through D8LooP?

No. The apply button opens the posting on the company site we fetched it from, with the time we last checked shown. We never host an apply form.

How do you know which skills a job asks for?

Every skill shows the sentence of the posting it was found in. A skill without evidence is not shown, and one that readers flag as wrong is hidden.

What happens when a company feed breaks?

That company shows fewer jobs, never stale ones: its roles age out normally and its page says when it was last checked. The state of every feed is on the companies page.

Which companies are included?

One hundred companies with real data platforms, from Amazon, Google and Netflix to Databricks, Stripe and Grab. The full list, with the state of each feed, is on the companies page.

Do you have every data engineering job?

No, on purpose. We cover Data Engineer, Analytics Engineer, Data Platform and Data Architect roles at the 100 companies, and nothing else.

How is the prep plan built?

Each skill in the posting maps to practice topics on D8LooP. The plan takes five drills per module at the level in the job title and closes with the interview questions for it.

Is it free?

Browsing and building a plan are free with an account. The drills follow the entitlements you already have.

Prepare for the job.
Not for the internet.

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