What does a Data Architect do?

A data architect owns major decisions around Data Modeling, Snowflake, AWS (Redshift, S3, Glue) and sets the technical direction for data & analytics projects. You'll spend your days splitting time between hands-on work, mentoring other team members, and working with stakeholders to figure out what's worth building next. This isn't a role where you just write specs and hand them off. You're expected to stay close to the work.

The people who do well in this role tend to be strong in SQL, Dimensional Modeling, Spark, but more importantly, they know how to figure out what they don't know. Data & Analytics moves fast, and the best data architects are the ones who can adapt without needing someone to hand them a playbook every time something changes.

Right now, data architect roles pay in the range of $140,000 - $200,000, and most positions are looking for senior 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 data architect

Before anything else, get solid on the fundamentals. For data architect roles, that means understanding Data Modeling and Snowflake 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 Data Modeling and Snowflake and AWS (Redshift, S3, Glue)

Reading docs and watching tutorials won't get you hired. You need to actually build things with Data Modeling and Snowflake and AWS (Redshift, S3, Glue). 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 AWS Certified Data

For data architect roles, certifications like AWS Certified Data Analytics - Specialty 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 data architect role

Most data architect positions are senior level and pay around $140,000 - $200,000. 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 data architect, you'll have options. Roles like Quantitative Analyst 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 data architect job postings. You don't need all of them on day one, but you should be working toward them.

Data ModelingSnowflakeAWS (Redshift, S3, Glue)SQLDimensional ModelingSparkTerraformdbtKafkaData Vault 2.0

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.

AWS Certified Data Analytics - Specialty

Snowflake SnowPro Advanced: Architect

DAMA CDMP Master