Data Engineer (BI)

Location: Remote; preference given to candidates on the U.S. East Coast, with occasional travel.

Company

hirify.global is hiring for a data engineering and business intelligence role supporting organization-wide analytics.

What you will do

• Design and maintain semantic data models, dimensional models, metrics layers, certified datasets, and business-friendly data products.
• Develop and optimize production dashboards, reports, workbooks, and self-service analytics in Sigma, with additional work in Power BI and Databricks dashboards.
• Define KPI standards, calculation logic, metric glossaries, workspace conventions, and governance practices.
• Build secure and efficient data pipelines, transformation logic, and integrations supporting analytics and AI/ML use cases.
• Implement row-level security, Entra ID-based access controls, encryption, masking, and other data security controls.
• Partner with architecture, engineering, analytics, and business stakeholders on data quality, observability, requirements, documentation, and BI adoption.

Requirements

• 3+ years of hands-on data engineering and/or business intelligence experience.
• Experience with Databricks, including DAB and Materialized Views.
• 3+ years designing semantic or dimensional data models and building dashboards and reports in a modern BI platform.
• 3+ years using analytical SQL, including ANSI SQL, T-SQL, or Spark SQL, and Python for pipeline construction, transformations, and automation.
• Experience with Azure DevOps and a bachelor’s degree in Computer Science, Information Technology, or a related field.
• Ability to work in an Agile-Scrum environment and produce comprehensive technical design documentation.

Nice to have

• Knowledge of GitHub Copilot.
• Experience with HIPAA-compliant datasets.
• Master’s degree in a relevant field.

Culture & Benefits

• Remote work with occasional travel.
• Collaboration across engineering, analytics, architecture, and business stakeholder groups.
• Opportunity to support governed self-service analytics and AI/ML capabilities across the organization.