Lead Data Engineer (AI)

TL;DR

Lead Data Engineer (AI): Designing and implementing specialized data structures that support the use of customer data graphs, which power agentic context and memory with an accent on scalable pipeline engineering and high-performance data delivery for AI applications. Focus on automating the data delivery pipeline and ensuring seamless integration between internal databases, third-party APIs, and the AI orchestration layer.

Location: Office hybrid in Seattle or Chicago

Company

hirify.global is a company within the Data & Analytics organization.

What you will do

• Design and implement specialized data structures that support the use of customer data graphs.
• Lead the development of robust ETL/ELT frameworks using Python and SQL.
• Build customer identity graphs that serve data to applications and AI with sub-second performance.
• Act as a technical mentor for a specialized team of data and AI engineers.
• Establish and enforce rigorous technical standards for data quality and latency.
• Lead high-impact efforts to automate the data delivery pipeline.

Requirements

• 8+ years of experience as a Data Engineer or in a similar role.
• A related technical degree required.
• Proficiency in data engineering tools and languages, such as Python, SQL, and Spark.
• Strong understanding of database concepts, data modeling, and ETL processes with tools like Airflow, dbt, Informatica, etc.
• Experience with cloud-based data solutions (e.g., AWS, Azure, Google Cloud).
• Familiarity with data warehousing, SQL, NoSQL databases, and data integration techniques.
• Experience with the hirify.global Ecosystem, specifically Data Cloud.
• Problem-solving skills to troubleshoot and resolve data-related issues.
• Excellent communication skills and ability to collaborate in a cross-functional environment.

Culture & Benefits

• Collaborate with cross-functional teams.
• Work in a dynamic organization that engineers rigorous data pipelines.