Data Engineer IV

TL;DR

Data Engineer IV (Cloud/Data Platforms): Building and optimizing data warehouses, pipelines, and distributed systems that transform complex datasets into reliable analytics and reporting outputs with an accent on scalability, data quality, governance, and security. Focus on designing resilient architectures, integrating cloud and streaming technologies, solving data-quality issues, and delivering actionable insights for U.S. defense and national security programs.

Location: Remote within the United States; active Secret clearance required.

Company

hirify.global is part of Aether Aerospace, a defense technology platform delivering advanced technologies, technology-enabled services, and manufacturing solutions to the U.S. Department of Defense and national security customers.

What you will do

• Build, maintain, and optimize data warehouses, pipelines, processing systems, and large-scale distributed data platforms.
• Collect, normalize, clean, structure, and analyze complex datasets from internal and external sources.
• Design scalable data solutions, architectures, policies, and practices supporting data protection, quality, delivery, and value.
• Investigate data-quality issues, perform root-cause analysis, resolve errors, and improve data processes and structures.
• Integrate tools, algorithms, cloud platforms, and data technologies with engineering teams.
• Define analytical approaches, produce operational reports, communicate findings to stakeholders, and support contractual deliverables.

Requirements

• Active Secret security clearance.
• Bachelor’s degree and 8–10 years of relevant experience.
• Advanced expertise in data warehouses, pipelines, and distributed data systems.
• Strong knowledge of databases, ETL/ELT frameworks, big data tools, data governance, metadata management, and security practices.
• Proficiency in Python, SQL, or Scala, with strong analytical and problem-solving skills.
• Experience with AWS, Azure, or GCP, containerization, and modern DevOps practices.

Nice to have

• Experience integrating machine learning algorithms into production data systems.
• Real-time data processing and streaming experience.
• Power BI, Tableau, or similar data visualization experience.
• Cloud, data engineering, or database certifications, including Google Cloud Data Engineer, AWS Data Analytics, or Azure Data Engineer Associate.
• Experience supporting government, defense, or contractual data environments.

Culture & Benefits

• Full-time permanent employment.
• Remote work arrangement.
• Collaboration with clients, business owners, engineering teams, and external stakeholders.
• Participation in company meetings and professional development planning.