DATA ENGINEER ROADMAP · STAGE 01 OF 04
SQL, Python, and data formats
Learn to read, query, validate, and transform common structured data.
Build small, testable data transformations and explain the shape of the data they produce.
CORE SKILLS
Key concepts in sql, python, and data formats
SQL querying
Use relational queries to filter, combine, summarize, and validate data for downstream use.
Topics include
- SELECT, WHERE, and GROUP BY
- Joins and window functions
- NULLs and query plans
Python for pipelines
Write maintainable scripts and modules for data extraction, transformation, and quality checks.
Topics include
- Functions and modules
- Exceptions and logging
- Testing transformations
Files and serialization
Choose and inspect storage formats based on schema, compatibility, and workload needs.
Topics include
- CSV and JSON
- Columnar formats such as Parquet
- Compression and schema evolution
Data quality basics
Detect missing, invalid, duplicated, or unexpected records before they create downstream errors.
Topics include
- Schema and type checks
- Uniqueness and null checks
- Freshness and volume checks
APPLY WHAT YOU LEARN
Practical project
Build a repeatable job that reads raw records, validates them, writes a clean output, and reports what it rejected and why.
CHECK YOUR UNDERSTANDING
You are ready to move on when
- Can explain input assumptions and output schema.
- Can rerun a failed job without silently duplicating or corrupting output.