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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.

Senior Analytics EngineerSenior

Faire · San Francisco, CA

PythonSQLWarehousingAirflow / orchestrationData modellingtoday4+ yrs

Senior Finance Analytics EngineerSenior

Faire · New York City, NY; San Francisco, CA

Airflow / orchestrationData modellingPythonSQLWarehousing1 d ago5+ yrs

Sr. Data & Analytics Engineer, Amazon LeoSenior

Amazon · Redmond, Washington, USA

Data modellingData qualityPythonSQLAWS6 d ago5+ yrs

Sr. Business Intelligence Engineer, AWS Analytics EngineeringSenior

Amazon · Seattle, Washington, USA

Data modellingSQLWarehousingAWSPython9 d ago5+ yrs

Senior Product Analytics Engineer - AdsSenior

Faire · San Francisco, CA

Data qualityPythonSQLWarehousingAirflow / orchestration11 d ago4+ yrs

Sr Analytics EngineerSenior

Delivery Hero · Montevideo, Montevideo Department, uy

Airflow / orchestrationData modellingSQLGCPDashboards & BI12 d ago

Sr Analytics EngineerSenior

Delivery Hero · Buenos Aires, ar

Airflow / orchestrationData modellingSQLGCPDashboards & BI12 d ago

Faire · boards.greenhouse.io · checked today

Senior Analytics Engineer

San Francisco, CASenior4+ yrsAnalytics Engineerposted today

Skills, with evidence

  • Python
    Production-level development experience in Python.must have
  • SQL
    Strong SQL skills with demonstrable competencies in designing well-architected data models and optimizing query performance.must have
  • Warehousing
    Deep experience and knowledge of data warehousing concepts, ETLs, big data technologies, and analytics platforms.must have
  • Airflow / orchestration
    Experience with Airflow, Docker, DBT or similar analytics workflow tools.
  • Data modelling
    <li>Lead the technical execution in building scalable data models and pipelines for a domain defining the architecture, feature requirements, roadmap.</li>
  • Data quality
    <li>Build data pipelines with rigorous approaches to data quality, validation, testing, and observability.</li>
  • Cost & performance
    <li>Optimize processes for operational excellence in project management and system reliability.</li>
  • dbt
    <li>Experience with Airflow, Docker, DBT or similar analytics workflow tools.</li>
  • Kubernetes
    <li>Experience with Airflow, Docker, DBT or similar analytics workflow tools.</li>not practised here
  • Machine learning
    At Faire, we're using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe.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 boards.greenhouse.io

leaves in 13 dremoved the moment Faire 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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