Data Engineer Roadmap
You build the pipelines that move, clean and serve data - the plumbing every analytics and AI team depends on. Indicative 2026 entry salaries $75-100k US, often reached via a first analyst or backend seat. SQL + Python + one warehouse is the hiring triangle.
By Carl Mills • Last updated • progress saves in your browser • free personalized PDF study plan.
Data Engineer roadmap FAQ
Data engineer vs backend engineer - which am I?
Both build server-side systems; data engineers optimise for moving and transforming large batches reliably (pipelines, warehouses), backend engineers for serving requests fast (APIs). If schemas and data quality excite you more than endpoints, you are a data engineer.
Which warehouse should I learn?
Concepts first (columnar storage, partitioning), then any one of Snowflake, BigQuery or Databricks - job listings decide which. Local Postgres + dbt teaches 80% of the thinking for free.
Do I need Spark?
For a first role, usually not - most companies have medium data, not big data. Know what Spark solves and when a warehouse + dbt is the simpler answer; genuine Spark depth can come on the job.
What next once the list is green?
Prove it under pressure: take the free Mock Interview, then check your application signals.
Not sure this is your direction?
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