Analyst Engineer (dbt)

Location: Madrid, Spain

Company

hirify.global provides employee benefits and engagement solutions focused on personalized and sustainable employee experiences.

What you will do

• Build and maintain production-grade data models that transform raw Bronze data into reliable Silver data layers.
• Design structured schemas with clear naming conventions, defined granularity, and documented business logic.
• Implement automated data quality controls, validations, tests, monitoring, and anomaly detection.
• Monitor data freshness, reliability, and performance, proactively resolving quality issues.
• Manage data model evolution through versioning, change management, and communication with downstream consumers.
• Collaborate with product engineers, central data engineers, the Data Council, and cross-functional stakeholders on data standards and governance.

Requirements

• Strong SQL skills, including window functions, CTEs, incremental processing patterns, and optimization techniques.
• Hands-on experience with dbt modeling, testing, documentation, macros, and package management.
• Strong understanding of dimensional modeling, schema design, snapshotting, and incremental approaches.
• Experience with Git, pull requests, code reviews, and CI/CD for data workflows.
• Ability to translate business requirements into scalable data models and communicate technical decisions clearly.
• Comfortable communicating in English and Spanish and working with multicultural teams.

Nice to have

• Experience with ClickHouse.

Culture & Benefits

• Work on employee benefits products serving millions of people and supporting local communities.
• Join a multicultural organization with 5,000 experts across 29 countries.
• Inclusive environment that values diversity, wellbeing, work-life balance, and equal opportunities.
• Opportunities to experiment, develop new skills, and grow professionally.
• Work on sustainability, diversity, and local-economy initiatives.

Hiring process

• Video call with a member of the People team.
• Discussion with the Product Manager and Engineering Manager.
• Technical conversation including a data modeling challenge covering SQL, dbt, and schema design.