30+ Data Engineer Jobs in Zürich

Automatisierung von Datenflüssen und Entwicklung von BI-Dashboards für Life, Non-Life und Investments. Erfahrung in Datenextraktion, Reporting-Automatisierung und SQL/Python erforderlich. Fokusverschiebung von Produktion zu Business-Insights.

Designing end-to-end data leverage solutions for high-profile clients. Over 7 years of data engineering experience with Python, R, or SQL required. Collaboration with senior stakeholders on high-impact projects.

Automated business document understanding, transforming messy documents into structured information. Python pipeline development experience required. Mentoring by senior consultants, access to D ONE Academy.

Designing and implementing RAG components in Python for data value creation. Experience with large datasets and cloud platforms required. Mentoring by senior consultants, access to D ONE Academy.

Designing, developing, and executing CRM data migration solutions for wealth management. Complex automation and validation script development skills required. Daily hands-on with large datasets and mission-critical systems.

Designing secure, governed, and scalable architectures on Databricks' Data Intelligence Platform for high-value customer accounts. 8+ years in solutions architecture or related senior technical role required. Orchestrating Databricks, customer, and partner teams for technical execution.

Developing complex EUC solutions with Python and MS Office for a sustainable private bank. Proficiency leveraging AI tools and expertise in relational data modeling required. Above average insurance coverage and meal allowance.

Advising automotive, chemical, and pharma clients on data-driven strategies and ML implementation roadmaps. 5-10 years consulting experience in data platforms and advanced analytics required. Partial remote work, flexible hours, and dedicated training budget.

Designing scalable cloud data platforms and AI solutions for clients. Translating business needs into data architectures using Databricks or Fabric. Bachelor's degree and industry domain knowledge required. International team, diverse backgrounds, and mentoring program.

Entwicklung von Data- und AI-Anwendungen bis zur Produktionsreife, inklusive Services und Agent-Teams. Erfahrung im Software Development Lifecycle mit AI-Komponenten und produktionsreifem Python erforderlich. Implementierung von Demos, PoCs und MVPs zur Greifbarmachung technischer Lösungsansätze.

Maintaining and developing the investment data warehouse with Azure Data Factory monitoring. 2-3 years data operations experience required. On-the-job development, access to learning resources.

Shaping enterprise data platforms and leading data quality initiatives for clients. Hands-on data governance or management experience required. Consulting experience in international, client-facing environments.

Productionizing data & AI solutions on the Databricks platform, owning end-to-end system architecture. 6+ years data engineering, Python/Scala/JS coding, and cloud ecosystem expertise required. Daily stand-ups, cross-functional collaboration.

Shaping enterprise-wide data capabilities for wealth management, influencing data management across the bank. Enterprise data catalogue platform experience required. Job alert setup.

Leading client engagements in data governance, quality, and AI-readiness for PwC's Cloud, Data & AI team. Strong expertise in enterprise data platforms and modern data architecture required. Focus on data strategy translation and scalable framework design.

Entwicklung tragfähiger Data- & AI-Lösungsarchitekturen für internationale Beratungsgruppe. Praktische Erfahrung mit produktiven AI-Lösungen im Enterprise-Umfeld erforderlich. Verbindung von Daten, AI-Modellen, Anwendungen, Schnittstellen und Infrastruktur.

Designing end-to-end cloud architectures with AI/GenAI and Kubernetes for diverse clients. 5+ years cloud architecture experience required. Consulting experience a plus.

Entwicklung und Betrieb der technischen Grundlagen für generative AI-Lösungen in einem Ingenieurbüro. Erfahrung im Aufbau moderner Daten- und AI-Lösungen mit Cloud-Architekturen (Azure) erforderlich. Gestaltungsspielraum und Mitgestaltung neuer Technologien.

Designing and maintaining data pipelines and backend services for decisioning and reporting. 5+ years of ETL/ELT and data warehousing experience required. Azure cloud-based data technologies, CI/CD environments.

Engineering AI and automation solutions for crypto finance use cases. Production experience with LLM applications and Python required. Hybrid role, international team.

Aufbau und Betrieb der analytischen Plattform für Einzelleben auf Basis von Microsoft Azure Synapse/Fabric. Hochschulabschluss in Informatik oder verwandtem Bereich erforderlich. Skalierbare Datenarchitekturen und Datenpipelines konzipieren.

Driving AI & Data strategy and development for global transformation partner. Consulting foundations and broad AI/data literacy required. Profit share and flexible working hours.

Defining technical vision and roadmap for large-scale data platforms at a wealth management firm. Proven experience scaling data platforms and hands-on exposure to modern data technologies required. Agile and DevOps practices, CI/CD pipelines, 4-day work week.

Designing and building GenAI/ML models for financial services clients. Practical GenAI and ML experience required. Work in regulated environments with large-scale data.