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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

Pick a job.
Get the plan.

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

Software Engineer III, Synthetic Data Engineer, XRSenior

Google · Munich, Germany

Machine learningPython7 d ago2+ yrs

Google · google.com · checked today

Software Engineer III, Synthetic Data Engineer, XR

Munich, GermanySenior2+ yrsData Engineerposted 7 d ago

Skills, with evidence

  • Machine learning
    1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).must have · not practised here
  • Python
    2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.must have

Your plan

  1. Python

    drills at the Senior level

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

See the full planApply on google.com

leaves in 6 dremoved the moment Google 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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