Engineering team lead állások, munkák adatbázisszakértő kategóriában

• Design and maintain robust, scalable data architectures
• Build and optimize high‑performance data models for analytics
• Partner with business and engineering teams to shape data solutions end‑to‑end
• Lead data integration, transformation, and migration efforts

• Define and develop tools for large scale data analysis using machine learning and AI for on-going insight, to drive TCO reduction.
• Plan roadmap for cloud resources adoption, based on price/performance, capacity and demand.
• Automatic classification and recommendations for optimal resource allocation.

• Define, design, and guide the implementation of platform solutions that enhance the reliability, security, and scalability of the Database Platform infrastructure.
• Provide technical leadership in cloud infrastructure, networking, CI/CD, and security for operational data storage solutions.

(Senior) Manager –AI Data Architect (m/w/d) Zürich/Basel/GenevaOne of the fastest growing business consultancy firms in Switzerland is looking for talented candidates like you.Is business consultancy your kind of work? Do you strive to achieve excellence in a customer centric environment? Then our...

Lead Data Scientist (f|m|d) | 100% | Hybrid working model | Zurich SwitzerlandCompany DescriptionWelcome to SMG Swiss Marketplace Group!SMG is a pioneering network of online marketplaces and a leading European digital company that simplifies people’s lives with forward-looking products.We operate...

Design and deploy advanced scoring engines for Leads and Opportunities Lead the development of Marketing Mix Modeling (MMM) and Multi-Touch Attribution (MTA) to quantify marketing ROI and guide budget allocation Develop algorithmic strategies for Value-Based Bidding (VBB) and customer acquisition...

Lead Data Science (f|m|d) | 100% | Hybrid working model | Zurich SwitzerlandCompany DescriptionWelcome to SMG Swiss Marketplace Group!SMG is a pioneering network of online marketplaces and a leading European digital company that simplifies people’s lives with forward-looking products.We operate...

• Combine curiosity, fast understanding of business processes, and strong analytical skills to identify and implement impactful Data Science solutions
• Lead end-to-end development and operationalization of Machine Learning models within a team of experienced Data Scientists and Data Engineers

Architect and implement cloud-native data solutions using GCP (BigQuery, Dataflow, Pub/Sub, Dataproc, Cloud Composer, Cloud Storage) Lead the design and development of complex data pipelines and distributed processing frameworks that ensure scalability, performance, and operational reliability...

• You will architect cloud and hardware solutions to scale AI workloads across GPUs and accelerators, optimizing storage and networking for maximum throughput and cost control.
• You will engineer and operate end-to-end AI systems, focusing on fine-tuning and scalable serving of modern AI models.

Lead or participate in scoping the engagement, designing high-level architecture, defining subtasks, and project delivery schedules Deliver projects independently or within a mixed DS/DE team setup, often as technical lead Act as client-facing interface or SPOC to customers Provide ML/DS...

• Support with the operation of the Azure-based platform (including Docker on Linux/Windows VMs) with team guidance
• Assist in building and documenting data pipelines (Azure Data Factory, Databricks catalogs)
• Help create and maintain Databricks notebooks (Python) for specialized use cases

• Build the backbone of Circonomit's technology and develop end-to-end features that deliver immediate value for our customers to map their reality into a semantic and computable model
• Build and refine high-quality, performant user interfaces with TypeScript and Solid.js

• Architect and build the high-performance backbone of our data platform
• Focus on distributed computing stability and building effective caching strategies for large-scale operations
• Design ETL pipelines and architect resilient caching for complex dependency resolutions

• Architect complex data flow solutions, enabling transparent, versioned, and fully auditable computations
• Design the data layer by developing metadata and data lineage models fused by semantic graphs and numerical data