D8LooP
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Jobs · 220 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.

Senior Data Platform EngineerSenior

Too Good To Go · Copenhagen, Denmark · Remote

Airflow / orchestrationPythonSQLSparkdbt8 d ago

Data Platform EngineerMid

Too Good To Go · Copenhagen, Denmark · Remote

Airflow / orchestrationData qualityPythonSQLSpark10 d ago

Too Good To Go · jobs.ashbyhq.com · checked today

Senior Data Platform Engineer

Copenhagen, DenmarkSenior · RemoteData Platformposted 8 d ago

Skills, with evidence

  • Airflow / orchestration
    Extensive experience designing, building, and operating data processing solutions (Airflow, AppFlow, Metaflow, dbt, dlt), and working with distributed systems in production (Spark on EMR, Glue).must have
  • Python
    Data Engineering: Deep proficiency in Python and SQL, advanced understanding of modern data warehouse internals (AWS Redshift), efficient ways of working on S3, and strong data engineering fundamentals including scalability, reliability, fault tolerance, and trade-off analysis.must have
  • SQL
    Data Engineering: Deep proficiency in Python and SQL, advanced understanding of modern data warehouse internals (AWS Redshift), efficient ways of working on S3, and strong data engineering fundamentals including scalability, reliability, fault tolerance, and trade-off analysis.must have
  • Spark
    Extensive experience designing, building, and operating data processing solutions (Airflow, AppFlow, Metaflow, dbt, dlt), and working with distributed systems in production (Spark on EMR, Glue).must have
  • dbt
    Extensive experience designing, building, and operating data processing solutions (Airflow, AppFlow, Metaflow, dbt, dlt), and working with distributed systems in production (Spark on EMR, Glue).must have
  • AWS
    Optimize system performance, efficiency, and infrastructure cost governance across our AWS data ecosystem.must have · not practised here
  • Terraform
    Experience applying DataOps, GitOps, Terraform, CI/CD tools (GitHub Actions, Docker), and observability tools.must have · not practised here
  • Streaming
    Data Platform enables multiple teams including Backend, ML, Analytics, and Marketing by helping them manage data infrastructure powering batch pipelines, live inference, and streaming initiatives across the company.
  • Data quality
    - Automate observability metrics, monitoring, and data integrity tests to ensure reliable, trusted data sources and strong data governance across central warehouse and external team product workflows.
  • Failure handling
    - Automate observability metrics, monitoring, and data integrity tests to ensure reliable, trusted data sources and strong data governance across central warehouse and external team product workflows.
  • Warehousing
    - Automate observability metrics, monitoring, and data integrity tests to ensure reliable, trusted data sources and strong data governance across central warehouse and external team product workflows.
  • Dashboards & BI
    You will be responsible for designing, improving, and implementing reliable, robust data systems and the ingestion flows that feed both our backend app and our BI tools, supporting growth and better decisions across the company.not practised here
  • Governance & security
    - Optimize system performance, efficiency, and infrastructure cost governance across our AWS data ecosystem.not practised here
  • Kubernetes
    Experience applying DataOps, GitOps, Terraform, CI/CD tools (GitHub Actions, Docker), and observability tools.not practised here

Your plan

  1. SQL

    drills at the Senior level

  2. Python

    drills at the Senior level

  3. Modelling

    drills at the Senior level

  4. Pipelines

    drills at the Senior level

  5. Spark

    drills at the Senior level

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

See the full planApply on jobs.ashbyhq.com

leaves in 5 dremoved the moment Too Good To Go 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?

220 product companies with real data platforms, worldwide: Amazon, Google and Netflix; Databricks, Stripe and Anthropic; Spotify, Adyen, N26 and Trade Republic in Europe; Careem, Tamara and Bybit in the Gulf; Grab, Airwallex and PayPay in Asia-Pacific; Nubank and QuintoAndar in Latin America. The full list, with the state of each feed, is on the companies page.

What does “Jobs abroad with relocation support” show?

Roles outside India where moving is supported, on one of two kinds of evidence. “Relocation”: the posting itself offers relocation or visa support. “Relocates”: the company publicly relocates hires to that country (its relocation page, its careers page, or relocate.me), linked from the job page. A posting that refuses relocation or sponsorship never shows, whatever the company does in general. Always confirm the details with the recruiter before you plan a move.

Do you have every data engineering job?

No, on purpose. We cover Data Engineer, Analytics Engineer, Data Platform and Data Architect roles at these 220 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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