Introduction

This post outlines a practical roadmap for aspiring data engineers in 2026. We cover the key skills, tools, and milestones that will help you land a role or level up.

Core Skills

1. SQL – Start with standard SQL, then window functions and query optimization.
2. Python – Focus on data libraries: pandas, pyarrow, and basic scripting for orchestration.
3. Distributed systems – Understand batch vs streaming and at least one big-data framework (e.g. Spark).

Tools to Learn

| Area | Examples | | ----------- | --------------------------- | | Orchestration | Airflow, Dagster, Prefect | | Warehouses | BigQuery, Snowflake, Redshift | | Streaming | Kafka, Flink, ksqlDB |

Next Steps

• Build a small batch pipeline (e.g. ingest → transform → load into a warehouse).
• Add a streaming component (e.g. Kafka + consumer).
• Deploy and run everything with an orchestrator.

Good luck on your data engineering journey. For more study tips, check out Flinote.