Week 1 · 8h
Pipeline Foundations
Outline
- · Why data engineering as a career — comp + roles + market
- · The modern data stack in 2026 (Fivetran/Airbyte → Snowflake/BigQuery → dbt → Lightdash/Mode)
- · Setting up your local dev environment (Python 3.12, uv, ruff, dbt-core)
- · Reading actual production pipelines on GitHub
Deliverable
Local dev environment + a working dbt-core project running on a sample schema
Required reading
Designing Data-Intensive Applications, Ch.1-3
Week 2 · 9h
SQL for Data Engineers
Outline
- · Window functions you actually use in pipelines
- · CTEs vs subqueries vs temp tables — when each matters
- · Performance reading: explain plans + cost analysis
- · Common modeling patterns (incremental, snapshots, slowly-changing dimensions)
Deliverable
Five end-to-end SQL exercises against the cohort warehouse + peer-graded review
Required reading
Snowflake docs: query optimization + clustering keys
Weeks 3-4 · 16h
dbt Modeling
Outline
- · staging / intermediate / mart layer pattern
- · Tests, docs, and lineage as first-class artifacts
- · macros + jinja for reusable transforms
- · incremental models: when, why, and the failure modes
Deliverable
A dbt project modeling a real e-commerce data warehouse — staging through marts, tests passing, docs deployed
Required reading
dbt fundamentals + The dbt Coalition Guide
Week 5 · 8h
Orchestration with Airflow
Outline
- · DAG design patterns — the ones that survive at scale
- · Operator vs Sensor choice + idempotency discipline
- · Backfills + retries + alerting
- · Why teams move off Airflow (and where they go: Dagster, Prefect, Temporal)
Deliverable
A 4-DAG project orchestrating dbt runs + sensor patterns + backfill workflow
Required reading
Airflow best practices guide + a Dagster comparison primer
Week 6 · 8h
Snowflake + Warehouse Architecture
Outline
- · Storage / compute separation in cloud DW
- · Cost optimization patterns (warehouse sizing, suspension, query tagging)
- · Data sharing + reverse ETL touchpoints
- · When to choose Snowflake vs BigQuery vs Redshift vs Databricks SQL
Deliverable
Cost-tagged warehouse setup with monitoring queries + a 1-page architecture review for your interview portfolio
Required reading
The Snowflake architecture paper + cost-management primer
Week 7 · 9h
Pipelines in Production
Outline
- · Observability: dbt + Monte Carlo + Datadog patterns
- · Failure modes and on-call runbooks
- · CI/CD for data — the testing pyramid for pipelines
- · Versioning: data contracts + schema-change protocols
Deliverable
Production-ready CI workflow on your capstone project + an alerting runbook
Required reading
Data Mesh + the Locally Optimal Data Engineer thesis
Week 8 · 6h
Career Transition
Outline
- · How data engineering interviews actually work in 2026
- · Resume + LinkedIn + take-home patterns that win
- · The recruiter call: what to ask, what to expect
- · Negotiation, comp benchmarking, and the offer cycle
Deliverable
Updated resume + portfolio + a 3-page take-home solved against the cohort rubric
Required reading
`Levels.fyi` data eng comp data + the negotiation playbook
Week 8 (parallel) · 0h
Capstone Review
Outline
- · Live capstone project review with the instructor + peer feedback
- · Mock interview practice with a senior data engineer alum
- · Networking session with the broader Quietshift alumni community
Deliverable
Capstone project graded against the rubric + a written instructor recommendation for your job search