Data Engineering Manager (AI)

Location: Remote, anywhere in the US; occasional all-company in-person meetings and up to 15 days of travel per year.

Salary: $180,000–$208,000 per year, depending on experience.

Company

hirify.global operates an AI-powered marketplace of skill-building courses and learning pathways, helping organizations develop skills and maintain compliance through learning content and enterprise integrations.

What you will do

• Lead and grow a lean data engineering team through 1:1s, performance management, mentorship, and career development.
• Guide delivery planning, prioritization, agile ceremonies, team operating rhythms, and continuous process improvement.
• Partner with analysts, business leaders, engineering, product management, and data consumers to translate business needs into reliable data solutions.
• Direct the design and scaling of the Snowflake-based data platform, ingestion architecture, and AI interface layers.
• Oversee ingestion from Salesforce, HubSpot, NetSuite, Zendesk, Jira, and Confluence into a centralized source of truth.
• Establish standards for data ownership, access management, lineage, testing, validation, monitoring, and pipeline observability.

Requirements

• Proven experience combining people management, technical leadership, architectural decision-making, and operational execution in data engineering.
• Experience designing scalable data systems, improving pipeline reliability, and building governed, accessible enterprise data assets.
• Experience with data platforms and tools such as Snowflake, Fivetran, dbt, and Looker, plus enterprise system integrations.
• Ability to communicate complex technical concepts in business terms and align cross-functional stakeholders.
• Must be based in the US and able to travel for occasional in-person meetings.

Culture & Benefits

• Remote-first work with company-wide in-person meetings several times a year.
• Comprehensive medical, dental, and vision coverage.
• Flexible paid time off, paid volunteer time off, and paid time off for learning and growth.
• 401(k) matching and incentive stock options.
• Professional development program and Employee Resource Groups.
• Daily use of AI tools with hands-on training and responsible experimentation guardrails.