Data Engineer (AI)

Location: Remote within the United States; all work must be performed in the U.S. Occasional onsite meetings are required at the client site in Washington, DC. Foreign locations and foreign IP addresses are blocked, and personal VPN connections are prohibited.

Salary: $81,499–$138,549 per year.

Company

hirify.global is an advisory and technology services provider delivering cloud, cybersecurity, enterprise architecture, data modernization, and digital transformation solutions to federal clients.

What you will do

• Build and maintain data pipelines, transformations, semantic views, conformed dimensions, and consumption-ready data models.
• Develop ETL/ELT workflows using Databricks, SQL, Python, Spark, Azure Data Factory, and orchestration frameworks.
• Implement pipeline documentation, metadata, lineage support, quality checks, automated testing, and release-readiness evidence.
• Design and support Lakehouse architectures, data products, and analytical datasets for reporting, self-service BI, and AI/ML use cases.
• Resolve data defects and document work products, decisions, risks, and operational evidence.
• Collaborate with data owners, governance, security, engineering, product, quality, and customer-facing stakeholders.

Requirements

• U.S. citizenship, U.S. residence, and authorization to work in the U.S. are required.
• Must have lived in the U.S. for three full years out of the last five years.
• Bachelor’s degree in a relevant technical field, or a high school diploma with four additional years of relevant experience; a master’s degree may substitute for two years of experience.
• At least three years of relevant experience aligned with the role’s responsibilities.
• Strong experience with Databricks, Delta Lake, Apache Spark, SQL, Python, cloud data pipelines, data modeling, and data quality controls.
• Experience with data governance, metadata and lineage, CI/CD, DataOps, MLOps, analytical platforms, or regulated environments.

Nice to have

• Experience with Unity Catalog, Azure Machine Learning, Azure storage services, Azure Event Hubs, Power BI, or comparable cloud-native data services.
• Experience supporting federal government or healthcare environments.
• Experience with Agile, DataOps, DevSecOps, predictive analytics, NLP, or generative AI workloads.

Culture & Benefits

• Full-time employment with a nationwide remote work arrangement within the United States.
• Occasional onsite collaboration at the Washington, DC client site.
• Work focused on modernizing a large federal agency’s enterprise data and analytics ecosystem.
• Collaborative delivery across technical, governance, security, quality, and customer-facing disciplines.