Hybrid Advanced Analytics Engineer – Data Pipelines & AI

Oliver Wyman; Lisboa; Hybrid; EUR 60,000 - 90,000; Full time

Job summary

Oliver Wyman in Lisbon is building a new data hub and seeks an Advanced Analytics Engineer to design scalable data solutions for analytics, ML and AI initiatives. You will develop data pipelines using PySpark and Databricks, ingesting structured and unstructured data to enable data-driven decision making.

Collaborate with AI engineers, data scientists and business stakeholders to deliver repeatable data models and DataOps practices. This hybrid role requires three days in the office weekly.

Qualifications

• 2+ years of experience in Data Engineering or Analytics Engineering.
• Strong hands-on experience with Python, PySpark, Databricks, and SQL.
• Experience designing scalable ETL/ELT pipelines and working with structured, semi-structured, and unstructured data.

Responsibilities

• Design, develop, and optimize scalable data pipelines using PySpark and Databricks.
• Build workflows to 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, platform teams, and data scientists to support AI-driven workflows.
• Implement data quality, governance, monitoring, and observability best practices.
• Optimize performance and scalability of distributed data processing environments.
• Support batch and real-time data processing architectures.
• Contribute to CI/CD pipelines and DataOps best practices.
• Document technical solutions, workflows, and procedures.

Skills

Python

PySpark

Databricks

SQL

APIs

CI/CD

Cloud familiarity

Tools

Databricks

SQL tooling

APIs integration

Job description

Oliver Wyman in Lisbon is building a new data hub and seeks an Advanced Analytics Engineer to design scalable data solutions for analytics, ML and AI initiatives. You will develop data pipelines using PySpark and Databricks, ingesting structured and unstructured data to enable data-driven decision making.

Collaborate with AI engineers, data scientists and business stakeholders to deliver repeatable data models and DataOps practices. This hybrid role requires three days in the office weekly.