What does a Analytics Engineer do?

A analytics engineer works across dbt, SQL, Snowflake/BigQuery to build and maintain systems in data & analytics. Day-to-day, you'll be writing code, reviewing pull requests, debugging production issues, and collaborating with product and design teams. It's the kind of role where you need to balance getting things done with doing them well.

The people who do well in this role tend to be strong in Python, Git, Data Modeling (Kimball/OBT), but more importantly, they know how to figure out what they don't know. Data & Analytics moves fast, and the best analytics engineers are the ones who can adapt without needing someone to hand them a playbook every time something changes.

Right now, analytics engineer roles pay in the range of $110,000 - $160,000, and most positions are looking for mid-level candidates. It's a competitive field, but companies are hiring. If you've got the right skills and can show real project work, you're in a strong position.

How to get there

Build your foundation in analytics engineer

Before anything else, get solid on the fundamentals. For analytics engineer roles, that means understanding dbt and SQL at a level where you can explain them to someone else. Don't try to learn everything at once. Pick the core topics that show up in every job posting for this role and get genuinely good at them.

Get hands-on with dbt and SQL and Snowflake/BigQuery

Reading docs and watching tutorials won't get you hired. You need to actually build things with dbt and SQL and Snowflake/BigQuery. Set aside time every week to write code, run experiments, or practice in a real environment. Hiring managers can tell the difference between someone who has used a tool and someone who has just read about it.

Work on real projects

Find a messy dataset and clean it, analyze it, and present your findings. Kaggle competitions work, but a self-directed project stands out more. The goal is to have something concrete you can talk about in interviews. "I built X, it does Y, and here's what I learned" is worth more than any course certificate.

Get certified in dbt Analytics Engineering

For analytics engineer roles, certifications like dbt Analytics Engineering Certification actually carry weight with hiring managers. They won't get you the job on their own, but they signal that you've put in structured effort. If you're choosing between certifications, pick the one you see mentioned most in job postings for roles you want.

Target your first analytics engineer role

Most analytics engineer positions are mid-level and pay around $110,000 - $160,000. When you're applying, tailor your resume for each job. Use the exact skills and keywords from the posting. Don't be picky about company size or brand name early on. A role where you'll learn fast is more valuable than a prestigious name on your resume.

Grow from here

Once you've got a couple years as a analytics engineer, you'll have options. Roles like Quantitative Analyst, Data Architect, Decision Scientist are natural next steps in data & analytics. The key is to keep building depth in your specialty while picking up broader skills like leadership, architecture, and cross-team collaboration. Your career path isn't a straight line, but this gives you a strong starting point.

Skills you'll need

These are the skills that show up most often in analytics engineer job postings. You don't need all of them on day one, but you should be working toward them.

dbtSQLSnowflake/BigQueryPythonGitData Modeling (Kimball/OBT)Looker/TableauAirflowData Quality TestingSemantic LayerFivetran

Certifications that help

These won't get you hired on their own, but they show hiring managers you've put in real study time. Worth it if you're switching careers or don't have much experience yet.

dbt Analytics Engineering Certification

Google Professional Data Engineer