Analytics Engineer

Kisi Incorporated Filial · Stockholm, Sverige · full-time, permanent · På plats · för 9 dagar sedan

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Publicerad 5 oktober 2026 · Inläst från Arbetsförmedlingen
Varför ett CV för det här jobbet?

94% av arbetsgivarna säger att deras filter sållar bort kvalificerade kandidater vars CV inte matchar annonsens exakta kriterier (Harvard Business School, 2021).

  • De ser det de bad om, först. Den erfarenhet som matchar annonsen kommer först, med annonsens egna ord, så att den som skummar hittar det på några sekunder.
  • Det tar sig förbi programvaran. Många större arbetsgivare använder program som rangordnar CV:n efter hur väl de matchar annonsen, ofta innan någon har läst dem.
  • På annonsens språk. En annons skriven på engelska får ett CV på engelska, även när ditt är på svenska.
  • Dina fakta, inget påhittat. Din egen erfarenhet, omordnad och omformulerad. Det annonsen vill ha och ditt CV inte visar listas så att du kan lägga till det, bara om det stämmer. Du kontrollerar det innan du skickar det.
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About the role

The Analytics Engineer designs, builds and owns Kisi's trusted, AI-ready data and insights layer. Rather than fielding individual data requests, the role makes sure that people and AI tools across the company get correct, authorized and context-aware answers on their own, and measures how accurate and impactful those answers are.

Responsibilities

Data activation in operational tools. Deliver relevant, trusted data into the tools each team already uses (e.g. enriching HubSpot with data from Stripe, Chargebee, the Kisi API and other sources) so teams can act without requesting reports.

Trusted insights layer. Build and maintain a documented, semantically modeled layer that humans and AI can query for accurate answers. Encode business context (such as the Stripe to Chargebee migration) and surface known data-quality limitations alongside results.

Consolidation of reporting assets. Migrate existing dashboards, reports and connected Sheets onto the insights layer to create a single source of truth.

Self-serve audiences and ad-hoc requests. Enable teams to build targeted audiences and one-off data pulls themselves, including through AI tools, and handle remaining business requests as they arise.

Source coverage. Integrate the business data sources needed for complete insights, such as Google Analytics, Facebook Ads and other marketing platforms.

Data governance and access control. Ensure every consumer, human or AI, can only access data they are authorized to see, with role-based access across the insights layer, dashboards and AI integrations.

Quality and impact measurement. Maintain an accuracy benchmark of known-correct figures and track adoption, time saved and decisions supported.

Success looks like: Team members get the insights they need, right when they need them, and trust them.

Qualifications

Strong SQL and data modeling skills, including dimensional or semantic modeling in a cloud warehouse (BigQuery or similar)

Experience building and maintaining data pipelines and integrations with SaaS tools such as HubSpot, Stripe and Chargebee

Experience making data usable by AI tools and LLMs, including documentation, semantic layers and guardrails

Working knowledge of data governance and role-based access control

Ability to translate business questions into durable data products and to explain data limitations clearly to non-technical stakeholders

Arbetsgivare
Kisi Incorporated Filial
Ort
Stockholm, Sverige · På plats
Anställningsform
full-time, permanent