End-to-End Data Pipeline
A startup is unifying ecommerce orders and SaaS subscription data into one analytics platform. You ship the whole thing: a real warehouse target with a modeled star schema, dbt models with green `dbt test`, a scheduled Airflow DAG with incremental/CDC loads, a bigger dataset than the course sandboxes, CI on every push, and a portfolio README — then defend it live. This is the build data-engineering interviews are actually about.
What You Will Ship to GitHub
Hiring managers don't want to see another cookie-cutter Titanic or Iris tutorial. You will build a professional repository with modular scripts and executive business memos that demonstrate commercial analytical maturity.
What You Will Master
6 Guided Project Milestones
Repo setup + warehouse target + dataset landing
Repo hygiene, warehouse sandbox, and the bigger dataset staged raw.
Model the marts — star schema, SCD II, partitioning
Grain decisions, dim/fact DDL, SCD Type II, partition + cluster keys.
Ingestion — incremental loads + CDC
Core MilestoneAPI/files to Parquet to warehouse with watermarks and change capture.
Transform with dbt — models, tests, docs, contracts
Sources, staging, marts, and a fully green `dbt test` suite.
Orchestrate with Airflow — DAG, retries, backfills
Review Pass RequiredA real DAG: schedule, idempotent tasks, retries, documented backfill.
CI + README + observability + live defense
Review Pass RequiredGitHub Actions CI, portfolio README, monitoring, and the live defense.
ATS Keywords & Resume Ready Bullets
"Authored an end-to-end data analytics project on End-to-End Data Pipeline utilizing Python, PostgreSQL / Snowflake / BigQuery sandbox, dbt — delivered production-grade queries, cohort distributions, and an executive stakeholder summary published as a portfolio GitHub repository."
Reading & References
Ready to build and ship End-to-End Data Pipeline?
Instant access to cloud database credentials, milestones, and starter queries.
Free End-to-End Data Pipeline portfolio project — with AI review
Build a real end-to-end data pipeline project for your data analyst portfolio in your own public GitHub repo — free brief, starter template, and milestone guides. When your code is ready, the ₹99 pass gets every milestone reviewed against a fixed rubric (end to end data pipeline walkthrough included) and issues a verifiable certificate on completion.
Is the End-to-End Data Pipeline project free?
The full project brief, milestone guides, and starter template are free to audit. The AI-powered review pass and verified certificate unlock at ₹99.
Can I add the End-to-End Data Pipeline project to my resume and GitHub?
Yes — that is the point. You build in your own public GitHub repo, every milestone is reviewed against a fixed rubric, and the certificate links to the repo employers can inspect. Only list what is visible in your repo.
How long does the End-to-End Data Pipeline project take?
Most students finish the 6 milestones in 2–4 weekends. Milestones unlock in order, and you can re-submit any milestone that needs work.
Build your portfolio & get certified
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