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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 AI Data EngineerSenior

Mastercard · Pune, India

Airflow / orchestrationData modellingData qualityPythonSQLtoday

Senior Data EngineerSenior

Mastercard · Pune, India

Data modellingFailure handlingPythonSQLSpark7 d ago6+ yrs

Senior Data EngineerSenior

Okta · Bengaluru, India

Airflow / orchestrationData qualitySQLdbtAWS11 d ago5+ yrs

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

Senior AI Data Engineer

Pune, IndiaSeniorData Engineerposted today

Skills, with evidence

  • Airflow / orchestration
    Strong knowledge of workflow orchestration tools such as Apache Airflow, Azure Data Factory, or similar platformsmust have
  • Data modelling
    Solid understanding of data modeling, metadata management, data lineage, and enterprise data governancemust have
  • Data quality
    Ensure high standards of data quality through automated validation, profiling, lineage, observability, and monitoringmust have
  • Python
    Strong proficiency in Python, SQL, Spark, and distributed data processing frameworksmust have
  • SQL
    Strong proficiency in Python, SQL, Spark, and distributed data processing frameworksmust have
  • Spark
    Strong proficiency in Python, SQL, Spark, and distributed data processing frameworksmust have
  • Streaming
    Experience with streaming technologies such as Kafka, Kinesis, or Azure Event Hubs.must have
  • AWS
    Experience building cloud-native data platforms using AWS, Azure, or Google Cloud Platformmust have · not practised here
  • Azure
    Experience building cloud-native data platforms using AWS, Azure, or Google Cloud Platformmust have · not practised here
  • GCP
    Experience building cloud-native data platforms using AWS, Azure, or Google Cloud Platformmust have · not practised here
  • Failure handling
    - Ensure high standards of data quality through automated validation, profiling, lineage, observability, and monitoring
  • Governance & security
    Working closely with AI Engineers, Data Scientists, Platform Engineers, and Solution Architects, you will deliver secure, reliable, and high-performance data solutions while driving engineering best practices, data governance, and operational excellence across AI initiativesnot practised here
  • Machine learning
    As a Senior AI Data Engineer within Mastercard's AI Center of Excellence, you will lead the design, development, and optimization of enterprise data platforms and pipelines that enable scalable AI, machine learning, and Generative AI solutions.not practised here
  • Cost & performance
    - Build and optimize data architectures supporting LLMs, RAG, embeddings, vector databases, and AI knowledge repositories

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 mastercard.wd1.myworkdayjobs.com

leaves in 13 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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