Data Architect

The tool list, translated:

• Most of these words are just product names. Here's what each one does, grouped by job:
• Where the data lives: Snowflake (a cloud warehouse where huge amounts of company data sit) and Microsoft Azure (Microsoft's cloud).
• Getting data in: Fivetran (a tool that automatically pulls data from different sources into Snowflake).
• Cleaning and shaping the data: dbt (cleans and transforms data using SQL), SQL (the basic language to pull data — everyone in data has this), Python (for automation and heavier logic).
• Running it all on a schedule: Dagster (manages and schedules the data pipelines so they run automatically).
• Showing the results: Power BI (Microsoft's dashboard/report tool for the business side).
• "ETL/ELT pipelines" just means moving data from source → warehouse → cleaning it up. That's the whole flow above.

• The part that actually matters for sourcing (read this twice):
• Almost every data candidate will list Snowflake, SQL, Python, Azure, Power BI - these are common, so they don't tell us much. The real filter is dbt + Dagster + Fivetran together. Very few people use all three hands-on. If a profile shows that combo as their actual day-to-day work, that's a strong fit. If someone has just dumped every tool into their skills section but their real projects were on something else, skip them — Brillio cares about hands-on delivery, not keyword lists.

So the rule for the team: don't match on keywords, match on what the person actually built. The dbt + Dagster + Fivetran + Snowflake stack is the fingerprint.

The logistics to screen for:

This is on-site in Virginia Beach - not remote, not hybrid. Candidate must already be local or genuinely willing to relocate and be there in person. Title is Data Architect / Sr. Data Architect, so we're targeting senior profiles, not mid-level.