DataStack Daily

If you’re asking how to become a data engineer, here’s the blunt version: no hiring manager reads a certificate and thinks “this person can fix a broken pipeline.” They hire for one thing — can you move data from a source into a warehouse, transform it into something trustworthy, and keep it running? Everything here builds toward one end-to-end portfolio project that answers it directly. In this guide What a data engineer actually does The core skills you need in 2026 A realistic learning path, in order Build the portfolio project that proves you can do the job Certifications: do they matter? The job market and pay landscape Your first 90 days FAQ Quick answer: A data engineer builds and maintains the pipelines that move raw data from sources into a warehouse and shapes it into tables analysts can trust. To break in: learn SQL, then Python, then load data into a cloud warehouse, transform it with dbt, and orchestrat...

An analytics engineer is the person in the data team who owns the transformation layer — the clean, tested SQL models between raw ingested data and the dashboards analysts use. This guide covers what the job involves, how it differs from data engineering and analysis, and whether it’s right for you. In this guide What an analytics engineer is Analytics engineer vs data engineer vs data analyst What an analytics engineer does day to day The skills and tools you need A day in the life: tracing a broken revenue number How to become an analytics engineer Is analytics engineering a good career? Frequently asked questions Quick answer: An analytics engineer owns the transformation layer in the modern data stack — the dbt models, tests, and metric definitions that sit between raw data and the dashboards teams use. The role emerged with dbt and cloud warehouses, and fits between the data engineer (pipelines & infrastructure) and t...