Data Engineer (AI/ML)

Location: Remote within the United States, with a strong preference for candidates in the Washington, DC Metro Area and occasional onsite meetings at the client site in Washington, DC. All work must be performed in the U.S.; access from foreign locations and personal VPN connections are prohibited.

Salary: $81,499–$138,549 annually for full-time employment.

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.
• Apply ETL/ELT, SQL, Python, Databricks, Azure Data Factory or equivalent orchestration, and modern data modeling practices.
• Implement pipeline documentation, metadata and lineage support, quality checks, validation, exception handling, and defect resolution.
• Design and support Lakehouse architectures, enterprise data warehouse modernization, migration, and cloud transformation initiatives.
• Develop data products and analytical datasets for reporting, self-service BI, machine learning, predictive analytics, NLP, and generative AI.
• Collaborate with data owners, governance, product, engineering, security, quality, data science, and customer-facing stakeholders.

Requirements

• U.S. citizenship is required due to federal contract requirements.
• Must reside in the United States, be authorized to work in the United States, and have all work performed in the United States.
• Must have lived in the United States for three full years out of the last five years.
• Bachelor’s degree in computer science, data engineering, information systems, data science, statistics, software engineering, or a related field; a high school diploma with four additional years of relevant experience may substitute.
• At least three years of relevant experience; a master’s degree may substitute for two years of experience.
• Strong communication, analytical, problem-solving, organizational, and collaboration skills.

Nice to have

• Experience with Databricks, Delta Lake, Apache Spark, SQL, Python, Databricks Workflows, Azure Data Factory, Unity Catalog, and Azure data services.
• Experience with DataOps, MLOps, CI/CD, observability, monitoring, automated testing, and release-readiness processes.
• Experience supporting Power BI, semantic models, data governance, metadata management, and analytical consumption layers.
• Experience in federal government, healthcare, regulated environments, Agile, DataOps, or DevSecOps teams.

Culture & Benefits

• Remote work arrangement within the United States with occasional client-site meetings.
• Collaborative work across technical, governance, security, data science, and customer-facing teams.
• Work focused on mission-critical federal modernization and large-scale enterprise data and AI platforms.
• Full-time employment with compensation determined by experience, skills, certifications, education, location, and contract requirements.