Top Data & Analytics Jobs

Conduct primary (quantitative and qualitative) and secondary research, analyze large datasets, synthesize insights, develop client-ready presentations and deliverables, support go-to-market research products, and contribute to client communications and internal discussions from the Lisbon-based European team.

Join Mastercard as an Associate Consultant Intern in Performance Analytics to analyze large datasets, build propensity models, create visualizations, and synthesize insights using SQL/Python/R. Work in small teams, engage with clients, receive mentorship, participate in volunteer and networking activities, and gain exposure to business development and product management. Program starts January 2027 (part-time, hybrid).

Design and implement ETL/data automation using Alteryx and SQL, build Tableau dashboards, develop Power Platform solutions, manage Alteryx Server, gather requirements, deliver end-to-end analytics, and continuously improve reporting and data integration.

Design, build, and maintain scalable batch and near-real-time data pipelines and curated datasets. Enable ML-ready feature datasets, implement reliability patterns, ensure secure data handling and governance, and drive engineering best practices in collaboration with data science, platform, and BI stakeholders.

The Lead, Big Data Analytics & Engineering will oversee data engineering, analytics enablement, and collaboration across teams, focusing on high-quality data platforms and solutions.

Partner with product and engineering to analyze product data, define user stories, build MVP reports, monitor product performance, track KPIs, participate in Agile ceremonies, and contribute to product roadmaps and feature opportunities.

The team lead manages a team of analysts, shaping KPI frameworks and creating data pipelines to enhance customer success through analytics, insights, and team development.

Lead strategy, architecture, and delivery of a production-scale data platform enabling agentic AI and analytics. Design lakehouse, streaming, retrieval, vector/feature stores, MCP servers, and governance for low-latency, secure AI consumption. Partner with Applied AI, Product and Architecture, guide senior engineers, and ensure data quality, lineage, observability, and compliance for enterprise AI products.

Lead strategy, architecture, and delivery of Mastercard's data platform for analytics and agentic AI. Design lakehouse, streaming, retrieval, vector/feature stores, and MCP servers. Ensure governance, lineage, observability, and AI-specific controls. Partner with Applied AI, Product, and Security; guide and grow a senior data engineering team while remaining hands-on to unblock technical challenges.

Lead data engineering strategy and architecture for CNPF, building lakehouse, streaming, and event-driven platforms to enable agentic AI and analytics. Deliver MCP servers, retrieval pipelines, vector stores, feature/knowledge graphs, and governance for production-scale LLM consumption. Partner with Applied AI, Product, and Architecture; ensure data quality, lineage, observability, and security; mentor senior engineers.