Database Engineer

Location: Remote within the United States; occasional travel may be required in the DMV area.

Salary: USD $142,638–$190,000 per year.

Company

hirify.global provides AI-powered decision intelligence solutions for national security, supply chain management, and digital identity.

What you will do

• Build source adapters and connectors for APIs, legacy systems, databases, files, and event streams.
• Develop normalization, mapping, validation, enrichment, and standardization logic for a common risk-signal schema.
• Implement production-grade ETL/ELT pipelines with testing, observability, error handling, retries, and backfills.
• Produce and consume Kafka or equivalent streaming events for near-real-time signal delivery.
• Define and maintain data contracts, mappings, lineage, schema evolution handling, deduplication, and source reconciliation.
• Optimize pipeline throughput, latency, scalability, and operational reliability while maintaining technical documentation and runbooks.

Requirements

• Must currently reside in the United States.
• Must maintain an active Top Secret security clearance.
• Bachelor’s degree with 8–10 years of experience, or master’s degree with 6–8 years of experience.
• 3–5 years of data engineering experience building production-grade ingestion and transformation pipelines.
• Strong experience with API integrations, REST/API frameworks, and ETL/ELT development in complex environments.
• Experience integrating heterogeneous or legacy systems with inconsistent schemas and data quality.

Nice to have

• Solid SQL skills and familiarity with NoSQL databases.
• Proficiency in Python or Java for data services and transformation logic.
• Hands-on Kafka producer and consumer experience or equivalent event-streaming experience.
• AWS certification, graph database experience, or AWS Database Migration Service experience.

Culture & Benefits

• Remote work arrangement with possible travel in the DMV area.
• Work across data architecture, scoring and analytics, application, and domain subject-matter teams.
• Focus on maintainable, testable, observable, debuggable, and supportable production systems.