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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.

Principal Data Engineer (AWS, Databricks, Ai, ML Flow, Data Architecture, Apache Airflow)Staff

Mastercard · Pune, India

Airflow / orchestrationData modellingData qualityPythonSQL1 d ago12–18 yrs

Principal Data Engineer (AWS, Databricks, Ai, ML Flow, Data Architecture, Apache Airflow)Staff

Mastercard · Pune, India

Airflow / orchestrationData modellingData qualityPythonSQL1 d ago12–18 yrs

Senior Data ArchitectStaff

Adobe · 6 Locations

Data modellingData qualitySQLGovernance & securityPython3 d ago10+ yrs

Senior Forward Deployed Engineer (Technical Data Architect)Staff

Databricks · London, United Kingdom

PythonSparkScalaAWSAzure13 d ago

Data Engineer, Data Architecture and Engineering, gTech Strategy and OperationsStaff

Google · Gurugram, Haryana, India

PythonSQLData modellingSparkData quality13 d ago1+ yrs

Mastercard · mastercard.wd1.myworkdayjobs.com · checked today

Principal Data Engineer (AWS, Databricks, Ai, ML Flow, Data Architecture, Apache Airflow)

Pune, IndiaStaff12–18 yrsData Architectposted 1 d ago

Skills, with evidence

  • Airflow / orchestration
    Experience with workflow orchestration platforms such as Apache Airflow, Databricks Workflows, AWS Step Functions, Azure Data Factory, or similar technologies.must have
  • Data modelling
    Advanced SQL expertise, including data modeling, performance tuning, query optimization, and large-scale analytical processing.must have
  • Data quality
    Strong understanding of data governance, metadata management, lineage, quality frameworks, privacy controls, and access management.must have
  • Python
    Expert programming skills in Python, PySpark, and modern software engineering practices.must have
  • SQL
    Advanced SQL expertise, including data modeling, performance tuning, query optimization, and large-scale analytical processing.must have
  • Spark
    Strong hands-on experience with distributed data processing technologies such as Apache Spark and modern lakehouse platforms.must have
  • Streaming
    Experience building scalable batch and real-time data pipelines.must have
  • AWS
    Experience building and operating cloud-native data platforms in AWS, or Azure, or other enterprise cloud environments.must have · not practised here
  • Governance & security
    Implement data governance capabilities including quality controls, lineage, metadata management, cataloging, access control, retention, and compliance.must have · not practised here
  • Machine learning
    We are seeking a Principal Data Engineer to design and build the data foundations that power advanced analytics, machine learning, generative AI, and agentic AI solutions.not practised here
  • Cost & performance
    Optimize data workloads for performance, scalability, reliability, resiliency, and cost efficiency.
  • Azure
    Experience building and operating cloud-native data platforms in AWS, or Azure, or other enterprise cloud environments.not practised here
  • Warehousing
    Develop governed lakehouse and modern data platform architectures using cloud-native technologies and distributed data processing frameworks.
  • Terraform
    Experience implementing CI/CD, automated testing, version control, Infrastructure as Code, and platform automation.not practised here

Your plan

  1. SQL

    drills at the Staff level

  2. Python

    drills at the Staff level

  3. Modelling

    drills at the Staff level

  4. Pipelines

    drills at the Staff level

  5. Spark

    drills at the Staff level

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

See the full planApply on mastercard.wd1.myworkdayjobs.com

leaves in 12 dremoved the moment Mastercard 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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