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Data Engineer

You build the pipes that get data from where it is made to where it gets used, reliably, every day.

No degree needed Moderate to hard. The engineering is real, and so is the 3am pipeline failure.


Can I actually do this?

Open without a degree, and a common step up from data analysis. Demand is steady because every organisation with analysts needs someone keeping their data arriving. The path is unusually concrete: get genuinely good at SQL, learn Python, then learn to schedule and monitor a pipeline.

Who it suits. People who want their work to be depended on rather than looked at.

Runway. Around a year. SQL first, then a language, then orchestration.

Coming from another job?

Coming from analysis? You have been on the receiving end of bad pipelines, which is the best possible preparation for building good ones. Data Analyst Backend Developer

Also advertised as

  • Analytics Engineer
  • ETL Developer
  • Data Platform Engineer
  • Data Infrastructure Engineer

The route

Four stations, in order. Each one is a thing you finish before the next matters.

  1. Station one

    Learn it free

    Only the best few, deliberately. Every one of these is free to use — the pill on each card says exactly what is and isn't free.

    PostgreSQL — the official tutorial

    Free to learn · no certificate

    SQL is the floor and the ceiling of this job. Learn it against a real database rather than a web widget.

    Airflow 101 — building your first workflow

    Free to learn · no certificate

    Orchestration is what turns a script into a pipeline. Airflow is the most widely used tool for it and the docs are free.

    Python — the official tutorial

    Free to learn · no certificate

    The language nearly all of this is written in. Free, from the source.

    See the full catalog in the explorer →

  2. Station two

    Attest strategically

    Nothing named. Cloud vendors sell data-engineering certifications and they do appear in job listings, particularly for the specific cloud an employer already runs on. We are not recommending one here because which cloud matters more than the certificate does, and buying the wrong one is money gone. If you already know you are targeting one platform, look at that vendor's exam — otherwise build a pipeline instead.

    Nothing here is worth paying for

    No credential needed

    Nothing named. Cloud vendors sell data-engineering certifications and they do appear in job listings, particularly for the specific cloud an employer already runs on. We are not recommending one here because which cloud matters more than the certificate does, and buying the wrong one is money gone. If you already know you are targeting one platform, look at that vendor's exam — otherwise build a pipeline instead.

  3. Station three

    Prove it

    A certificate says you passed a test. These say you can do the job.

    A pipeline that runs on a schedule and does not need you

    Ingest something real on a timer, land it somewhere queryable, and let it run for a month. Show the failures it survived.

    Data quality checks that fail loudly

    Show what happens when the upstream data goes wrong. Silent bad data is the thing this job exists to prevent.

    A schema you designed and can defend

    Explain why the tables are shaped the way they are and what query pattern drove it.

  4. Station four

    Get hired

    Search these exact titles

    • data engineer
    • analytics engineer
    • ETL developer
    • data platform engineer

    Who hires for this. Any organisation with an analytics team, plus retail, finance, health and logistics, where the data volume forces the role to exist.

    A pipeline that has been running unattended for weeks is evidence of the part employers actually worry about. That is our reasoning about what is inspectable, not a verified hiring statistic.

    On salary

    We don't publish salary estimates. Numbers copied between blogs drift from reality, and a wrong number costs you real negotiating power. When we have a verified public source, it goes here with its date.


Where this route continues

· How we verify