Role roadmaps / Analytics Engineer Role flowchart
The dbt-shaped role: models, tests, CI, and a metric finance can reuse. Between analyst questions and engineer pipelines.
Also called: Analytics Developer, Metrics Engineer
You ship: Versioned marts, contracts, and a metric layer someone else can query.
8–16 weeks if you already write SQL
Roadmap Coding Interview Question bank Switch roleData Analyst BI Analyst Data Engineer Analytics Engineer Data Scientist ML Engineer MLOps Engineer AI Engineer Data Architect Nearby roles:Data Analyst , Data Engineer , BI Analyst
Checked skills
0% · click a node for concepts, stacks, access, and what to produce · drag to pan · Ctrl-scroll to zoom
− Fit + Clear checks
Start · Analytics Engineer Foundations SQL at mart grain Windows, grain tests, and anti-joins. You will write more SQL than the DE. Git as a team sport PRs, reviews, and why main is protected. Warehouse dialect Pruning, clustering, clones. Know who pays for the explore. Daily craft dbt the way CI survives Staging 1:1 with sources, marts at a grain, slim CI. Tests on grain unique + not_null on the grain. Relationships to dimensions. Fail the build. Docs that get read Descriptions, exposures, and a metric page a PM can open. How you ship Slim CI and defer Build what changed. Defer to prod for the rest. State artifacts. Source contracts Breaking a column should break CI, not a dashboard at 9am. Metrics, not workbooks One definition. Many consumers. Semantic layer when the org is ready. Career moves AE interview SQL, dbt structure, and “how do you stop two revenues?” Next role DE if you want streaming. Analyst lead if you want narrative. Architect if you want platforms. Keep practicing Study this node
SQL at mart grain Windows, grain tests, and anti-joins. You will write more SQL than the DE.
If you cannot say the grain, you are not ready to write the model.
SQL at mart grain. If you cannot say the grain, you are not ready to write the model.
Time to learn You will write more SQL than the DE. Treat the pad as the job.
Prerequisites Mart grain vs source grain Windows for latest What you need SQL tracks A dbt project Interview SQL Concepts to study Mart grain vs source grain Windows for “latest” and running metrics Anti-joins for quality marts Incremental models and unique keys Tech stacks dbt SQL — The jobWarehouse dialect — Pruning, clusteringThis site SQL tracks — The padHow to study Write one mart with unique+not_null on the grain. SQL interview questions; foundations + windows tracks. What to produce fct_orders grain in one sentence unique + not_null on that grain Practice on this site SQL questions; coding tracks Pitfalls A mart that is a SELECT * from bronze Grain that changes when a join is added Interview prompts Say the grain of fct_orders in one sentence. Links
Mark as done All Articles Stacks Practice Learn Pages
No results. Try analyst, numpy, snowflake, or roadmap.
↑↓ navigate↵ openesc closeAliases: sf, numpy, analyst, mlops
