Advanced Analytics Engineer: Databricks & AI Pipelines (Hybrid)

Marsh McLennan; Lisboa; Híbrido; EUR 45 000 - 75 000; Tempo integral

Resumo da oferta

Mercer in Lisbon is seeking an experienced Advanced Analytics Engineer to design and build scalable data solutions that support advanced analytics, machine learning, and AI initiatives. You will join us in establishing Oliver Wyman’s new Lisbon hub.

This role focuses on developing data pipelines and workflows for structured and unstructured data using Databricks, Python, and PySpark, and on collaborating with AI engineers and business stakeholders to enable data-driven innovation.

Qualificações

• 2+ years of experience in Data/Analytics Engineering or related roles.
• Strong hands-on experience with Python, PySpark, Databricks, and SQL.
• Experience building scalable ETL/ELT pipelines.
• Experience with structured, semi-structured, and unstructured data.
• Familiarity with cloud platforms (AWS/Azure/GCP).
• Knowledge of MCP integrations and AI-driven workflow architectures is a plus.

Responsabilidades

• Design, develop, and optimize scalable data pipelines using PySpark and Databricks.
• Ingest, process, and transform structured and unstructured data.
• Develop data models and reusable datasets for analytics and AI use cases.
• Integrate external systems and enterprise platforms through APIs and modern data interfaces.
• Collaborate with AI engineers and platform teams to support MCP integrations and AI-driven workflows.
• Document technical solutions, workflows, and operational procedures.

Conhecimentos

Python

PySpark

Databricks

SQL

ETL/ELT

APIs

Cloud platforms

Data modeling

CI/CD

Distributed computing

Descrição da oferta de emprego

Mercer in Lisbon is seeking an experienced Advanced Analytics Engineer to design and build scalable data solutions that support advanced analytics, machine learning, and AI initiatives. You will join us in establishing Oliver Wyman’s new Lisbon hub.

This role focuses on developing data pipelines and workflows for structured and unstructured data using Databricks, Python, and PySpark, and on collaborating with AI engineers and business stakeholders to enable data-driven innovation.