Analytics Engineer (Healthtech)

Location: Stockholm, Sweden; on-site at the Stockholm HQ

Company

hirify.global is a fast-scaling health-tech company building clinician-first healthcare software for medical notes and workflows.

What you will do

• Translate stakeholder questions into trustworthy answers, metrics, models, and workflows that improve decision-making.
• Build self-serve analytics surfaces and documentation so teams can answer questions independently.
• Own and evolve the production data layer, including dbt models, metrics, and semantic definitions.
• Proactively identify patterns, risks, and opportunities in the data.
• Ensure dataset and metric quality through testing, monitoring, and clear ownership.
• Contribute the analytics perspective to data platform, tooling, and capability decisions.

Requirements

• Excellent SQL skills.
• Experience in analytics engineering, data analytics, data engineering, or a closely related field.
• Hands-on production experience building and maintaining a modeling layer with dbt or an equivalent tool, including testing and documentation.
• Business-minded approach with the ability to understand stakeholder goals and challenge unclear questions.
• Strong communication skills for presenting to groups and explaining methods to non-technical stakeholders.
• Ability to work primarily from the Stockholm office and attend the on-site case presentation.

Nice to have

• Python for analysis, scripting, and lightweight tooling.
• Experience embedded with product, commercial, or finance teams.
• Experience in healthtech or another regulated environment handling sensitive data.
• Experience in early-stage startups or scaleups.

Culture & Benefits

• 30 days of paid vacation per year.
• Pension and a 5,000 SEK wellness allowance.
• Company stock options and a competitive salary.
• Social activities, off-sites, after-work events, and seasonal parties.
• Collaborative work with specialists in AI, healthcare, and engineering.
• Background check required because the role involves sensitive patient data.

Hiring process

• Screening interview with Talent Acquisition.
• Data team interview followed by a technical discussion with the Data team and Head of Data.
• Case presentation at the Stockholm office with a team lunch.