Senior Data Engineer, Analytics

Location: Hybrid in Chicago, San Francisco, or Palo Alto, United States; in-person attendance required Tuesdays and Thursdays.

Salary: $127,577–$170,102 in Chicago or $136,962–$182,616 in the San Francisco Bay Area, plus equity, benefits, and a company bonus program.

Company

hirify.global is an AI-native social platform serving more than 15 million monthly users and building data products that support analytics, machine learning, and product development.

What you will do

• Own critical business datasets end to end, from stakeholder requirements and data modeling through pipeline development, metric validation, and data quality.
• Build reliable analytical data models that power reporting, machine learning, and AI-driven tools such as Data Daddy.
• Develop reusable metrics, dimensional models, and semantic definitions for consistent data discovery and interpretation.
• Transform high-volume event data into production-ready datasets using modern data engineering and orchestration practices.
• Partner with Data Science, ML Engineering, Product, Analytics, and business stakeholders to deliver scalable data solutions.
• Use AI-assisted development tools and modern engineering practices to improve modeling, testing, and documentation.

Requirements

• Strong SQL skills and experience designing dimensional data models, defining business metrics, and supporting complex analytical questions.
• Experience building reliable production datasets from raw, high-volume event data in a modern cloud data warehouse.
• Experience with data transformations, orchestration tools such as Airflow, and data quality validation.
• Understanding of semantic layers, reusable metric definitions, and consistent business logic across datasets.
• Experience collaborating with data scientists, ML engineers, analysts, and business stakeholders.
• Daily experience using agentic coding tools such as Cursor, Codex, Claude Code, or similar tools.

Nice to have

• Experience with Snowflake, Airflow, dbt, or comparable data transformation and orchestration technologies.
• Experience building semantic layers with Looker, dbt Semantic Layer, or similar frameworks.
• Interest in using LLMs and AI agents to improve data discovery, understanding, and analysis.
• Comfort taking ownership of ambiguous problems and working directly with stakeholders.

Culture & Benefits

• Hybrid work with a focus on outcomes and sustainable performance.
• Full health, dental, and vision premium coverage for employees, with partial dependent coverage.
• Up to $300,000 in fertility and family-building support.
• 401(k) plan with a 6% match and immediate vesting.
• Equity, company bonus, flexible vacation, and two company-wide rest weeks annually.
• Gender-affirming care coverage, wellness and commuting support, and meal benefits.