Senior BI Engineer (AI)

Location: Givatayim, Israel; hybrid work model with flexibility to work part-time from home

Company

hirify.global provides digital-world data and solutions used by more than 13,000 customers to support digital strategy and business decisions.

What you will do

• Own end-to-end data modeling and build the trusted Source of Truth for strategic product and business decisions.
• Transform raw data into clean, intuitive tables and automated datasets for Product Analysts, Business Leads, Product, Marketing, and GTM teams.
• Define consistent metrics, protect data integrity, and ensure reliable reporting across product and business use cases.
• Design, build, test, document, and maintain production-grade dbt models using modular, version-controlled code.
• Use Git-based CI/CD workflows, pull requests, automated tests, code reviews, and deployments for analytics code.
• Build AI-ready data foundations and participate in developing agentic solutions, partnering with AI and Data Service specialists.

Requirements

• 5+ years of experience in a relevant analytics or technical role such as Analytics Engineer, BI Engineer, BI Developer, or Data Engineer.
• Expert-level SQL skills, including complex query writing, performance optimization, and debugging legacy code.
• Hands-on dbt experience, including Jinja templating, incremental models, and package management.
• Experience with ETL processes, data warehousing concepts, and data modeling methodologies, including Amazon Redshift or Snowflake.
• Understanding of SaaS metrics such as ARR, funnels, and activation, and how data logic affects product growth and strategy.
• Hands-on experience with Git and CI workflows for data projects, including pull-request reviews, automated tests, and automated dbt deployments.
• Day-to-day experience using AI coding tools such as Cursor or Claude Code, with the ability to review and validate AI-generated code before release.
• Experience with Python for data orchestration or custom transformations.

Nice to have

• Experience with orchestration tools such as Airflow, Dagster, or Prefect.
• Experience with automated data tests, data contracts, monitoring, and alerting.
• Experience building data foundations for LLMs or AI agents, including semantic or metrics layers, text-to-SQL, or MCP-based data access.
• Experience tuning queries, models, and warehouse usage for analytical performance and cost efficiency.
• Experience with similar tools to Redshift, dbt, Databricks, Airflow, GitLab, and Cursor.

Culture & Benefits

• Hybrid work with face-to-face collaboration in the office and flexibility to work part-time from home.
• Inclusive, innovative, and supportive environment with open dialogue and encouragement of new ideas.
• Exposure to cutting-edge data-stack technologies, AI implementation, and high-scale data logic.
• Competitive compensation, comprehensive equity packages, well-being support, and team-bonding opportunities.