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Data Engineering

Data Engineer

Build the pipelines and platforms that move and shape data: SQL, Python, warehouses, batch and streaming ETL, and orchestration.

SQLPythonSparkAirflowdbt
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1

SQL & Python foundations

Advanced SQL

Essential

Python for data (pandas, scripting)

Essential

Linux & version control

Recommended
2

Data modeling & warehouses

Dimensional modeling (star/snowflake schemas)

Essential

Cloud data warehouses (BigQuery, Snowflake, Redshift)

Recommended
Build it

Model a raw dataset into a star schema

intermediate

Take messy source tables and design fact/dimension tables for analytics.

3

Building ETL/ELT pipelines

Batch processing & transformation (dbt)

Essential

Workflow orchestration (Airflow)

Recommended

Distributed processing (Spark)

Optional
Build it

Build an end-to-end ELT pipeline

advanced

Ingest raw data, transform it with dbt, and schedule it with Airflow.

4

Streaming & data quality

Streaming data (Kafka basics)

Optional

Data quality & testing

Recommended

Land the job

Turn the skills you built into offers โ€” resume, tailoring, applications, and interview prep.

Build a recruiter-ready resume

Essential

Use the builder to produce a clean, ATS-friendly resume from your career memory.

Go

Tailor your resume to each role

Recommended

Match keywords and highlight the experience each job actually asks for.

Go

Browse and apply to open roles

Essential

Find roles that match the skills on this path and apply with your tailored resume.

Go

Prep for interviews

Essential

Practice coding, system design, and behavioral rounds with AI-driven mock interviews.

Go