{"id":4020382,"url":"https://alion.io/job/callista-senior-data-engineer-datenplattform","title":"Senior Data Engineer Datenplattform","company":{"id":693135,"name":"Callista","domain":"callista.ch","url":"https://alion.io/company/callista-3","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Recruitee","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"freelance","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Lucerne, Switzerland"],"countries":["CH"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Data Vault","optional":false},{"name":"Databricks","optional":false},{"name":"dbt","optional":false},{"name":"Git","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-11-10T13:50:23Z","employer_posted_date":"2026-11-10","last_verified_at":"2026-11-11T00:49:55Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Für die Weiterentwicklung einer modernen Datenplattform auf Databricks sucht ein Agile Release Train im Bereich Data & Analytics bei einer Krankenversicherung erfahrene Data Engineers. Im Fokus stehen skalierbare Datenpipelines und Datenprodukte, die Umsetzung von Data-Vault-Modellen und der stabile, wirtschaftliche Betrieb der Datenlösungen im Azure-Umfeld. Du arbeitest als Teil des Data-Teams und bringst die Plattform mit deiner Erfahrung in Databricks, dbt Core und Data Vault technisch voran.\nAufgaben\nEntwicklung und Betrieb skalierbarer Datenpipelines und Datenprodukte auf Databricks\n\nUmsetzung von Datenmodellen nach Data Vault 2.0 inkl. historisierter und dimensionaler Modelle\n\nEntwicklung von Transformationen, Datenqualitätstests und Dokumentation mit dbt Core\n\nWeiterentwicklung der Datenplattform mit Python, SQL und Apache Spark / PySpark\n\nAufbau und Pflege von CI/CD-Prozessen sowie automatisierten Tests\n\nSicherstellung eines stabilen und wirtschaftlichen Betriebs der Datenlösungen im Azure-Umfeld\n\nZusammenarbeit im agilen Team und aktive Mitwirkung an der Weiterentwicklung der Plattform\n\nRequirements\nMindestens 5 Jahre Berufserfahrung im Data Engineering, idealerweise mehrjährig im Konzernumfeld\n\nFundierte Kenntnisse in Databricks, SQL, Python und Apache Spark / PySpark sowie Erfahrung in der Entwicklung und im Betrieb skalierbarer Datenpipelines\n\nFundierte Erfahrung mit dbt Core auf Databricks und in der Datenmodellierung nach Data Vault 2.0, inkl. historisierter und dimensionaler Datenmodelle, Datenqualitätstests und Dokumentation\n\nErfahrung mit Git, CI/CD und automatisierten Tests\n\nSichere Arbeitsweise in agilen Teams, Erfahrung mit SAFe von Vorteil\n\nDomänenerfahrung im Krankenversicherungsbereich von Vorteil\n\nHohe Eigenverantwortung sowie eine selbstständige, strukturierte und lösungsorientierte Arbeitsweise\n\nAusgeprägte Lernbereitschaft und die Fähigkeit, komplexe Sachverhalte selbstständig zu analysieren und neue Technologien rasch anzuwenden\n\nKommunikationsstärke, Teamfähigkeit und die nötige Ruhe, um auch unter Zeitdruck fundierte technische Entscheidungen zu vertreten\n\nGenerelle Rahmenbedingungen\nStart: Ab sofort\n\nDauer: bis 31.12.2027 (Option auf Verlängerung)\n\nPensum: 80-100 %\n\nArbeitsort: Luzern\n\nRemote: Max. 3 Tage pro Woche (Präsenz am Dienstag Pflicht, 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