Data Engineer (Middle)

TL;DR

Data Engineer (Middle) (Snowflake/dbt/SQL): Build and maintain data pipelines that move messy source data into Snowflake, shape it into usable datasets, and keep it reliable with strong SQL-driven transformations. Focus on debugging end-to-end data issues, writing dbt models with tests and documentation, and handling incidents and backfills to ensure production data stays correct.

Company

hirify.global provides cloud communications and collaboration technology.

What you will do

• Build and fix data pipelines for ingestion, transformation, and consumption.
• Develop dbt models with tests and documentation.
• Investigate data problems from reports back to the source systems.
• Respond to incidents (e.g., MSSQL job failures, Snowflake task hangs, missing S3 files) and implement fixes.
• Run backfills, validate results, and confirm fixes work.
• Monitor pipelines and data flows to prevent issues from reaching users.

Requirements

• Location: All candidates must be located in Republic of Georgia.
• 3–5 years of data engineering, data analysis, or a closely related role.
• Strong SQL skills (joins, window functions, CTEs) and ability to diagnose slow queries.
• Experience shipping production data work with a real database (MSSQL, Oracle, PostgreSQL, or similar).
• Understanding of data layers (raw → staging → consumption) and why shortcuts hurt.
• Comfort with incremental loads (watermarks, MERGE vs INSERT) and trade-offs.

Culture & Benefits

• Hybrid workplace type.
• Full ownership from day one with work that others can pick up quickly.
• Friendly team across different countries, continents, and time zones.
• AI tools are part of the culture (used daily for coding, debugging, and documentation).
• Room to grow in any direction.

Hiring process

• Stage 1: Applied → Stage 2: Review → Stage 3: Interview → Stage 5: Hired.