Data Engineer (Cloud Data Warehouse)

TL;DR

Data Engineer (Cloud Data Warehouse): Designing and building a scalable cloud data warehouse and automated ETL/ELT pipelines with an accent on dimensional modeling and database performance. Focus on optimizing SQL queries and creating analytics-ready datasets to enable business intelligence.

Location: Remote

Company

hirify.global is an educational technology company building a scalable foundation for data and analytics.

What you will do

• Assess the current data environment and recommend a scalable cloud data warehouse architecture.
• Design, build, and optimize a cloud data warehouse and supporting data models.
• Develop and maintain automated ETL/ELT pipelines from multiple data sources.
• Create analytics-ready datasets using dimensional modeling (star/snowflake schemas).
• Optimize SQL queries and database performance to ensure data quality and integrity.
• Document the data architecture, pipelines, and models to provide a roadmap for future scalability.

Requirements

• 5+ years of experience in Data Warehouse Engineering or Data Engineering.
• Advanced SQL skills with a proven track record of optimizing complex queries.
• Hands-on experience implementing cloud data warehouse solutions (e.g., Snowflake, Redshift, BigQuery, or Azure Synapse).
• Solid understanding of dimensional data modeling and version control using Git.
• Experience designing scalable data architectures.

Nice to have

• Experience with Python and orchestration tools such as dbt, Apache Airflow, Azure Data Factory, or AWS Glue.
• Proficiency with cloud platforms (AWS, Azure, or Google Cloud).
• Familiarity with BI tools like Power BI, Tableau, QuickSight, or Looker.
• Experience integrating data from APIs, SaaS applications, and relational databases.

Culture & Benefits

• Fully remote work arrangement.
• Direct collaboration and reporting line to the CEO.
• Opportunity to lead a high-impact, short-term infrastructure project.