Advanced Analytics Engineer

Oliver Wyman; Lisboa; On-site; 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

About Oliver Wyman

Oliver Wyman, a Marsh (NYSE: MRSH) business, is a management consulting firm driven by deep industry insight, bold innovation, and a collaborative approach that cuts through complexity to help organizations navigate their most defining transformative moments.

About Oliver Wyman

Oliver Wyman, a Marsh (NYSE: MRSH) business, is a management consulting firm driven by deep industry insight, bold innovation, and a collaborative approach that cuts through complexity to help organizations navigate their most defining transformative moments.

For more information, visitoliverwyman.com, or follow us onLinkedInandX.

This is a hybrid role that has a requirement of working at least three days a week in the office.

Job Overview:

We are seeking an experienced Advanced Analytics Engineer to design and build scalable data solutions that support advanced analytics, machine learning, and AI initiatives. You will be joining us in building Oliver Wyman’s new hub in Lisbon.

This role focuses on developing data pipelines and workflows for structured and unstructured data using Databricks, Python, and PySpark. The ideal candidate is passionate about modern data platforms, distributed computing, API integrations, and enabling data-driven innovation across the organization.

We will count on you to:

• 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 and platform teams to support MCP (Model Context Protocol) integrations and AI-driven workflows
• Collaborate with data scientists, AI engineers, and business stakeholders to support advanced analytics initiatives
• 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 operational procedures
  
  

What makes you stand out?

• 2+ years of experience in Data Engineering, Analytics Engineering, or related roles
• Strong hands-on experience with Python, PySpark, Databricks, and SQL
• Experience designing and developing scalable ETL/ELT pipelines and distributed data processing solutions
• Experience working with structured, semi-structured, and unstructured data
• Experience building and integrating APIs and enterprise data services
• Experience supporting advanced analytics, AI, or machine learning initiatives
• Strong understanding of modern lakehouse and cloud-based data architectures
• Experience with workflow orchestration, automation, and CI/CD pipelines
• Familiarity with cloud platforms such as AWS, Azure, or GCP
• Experience with streaming and real-time processing technologies is a plus
• Knowledge of MCP integrations and AI-driven workflow architectures is a plus
  
  

Skills and Attributes:

• Excellent problem-solving and analytical thinking skills with ability to solve complex data challenges
• Strong ability to design scalable and efficient data solutions in fast-paced environments
• Self-starter with strong ownership mindset and ability to work independently with minimal supervision
• Strong curiosity and desire to learn emerging technologies and modern data/AI practices
• Ability to interpret data trends and generate actionable insights for technical and business stakeholders
• Strong collaboration skills with ability to work effectively across engineering, analytics, AI, and business teams
• Effective communication skills with ability to explain technical concepts to non-technical audiences
• Strong attention to detail with focus on data quality, reliability, and operational excellence
• Ability to manage multiple priorities and adapt quickly to changing business needs
• Strong relationship-building skills and ability to influence stakeholders across the organization
• Passion for innovation, automation, and continuous improvement
• Ability to thrive in highly dynamic and evolving technology environments
  
  

Why join our team:

• We help you be your best through professional development opportunities, interesting work and supportive leaders.
• We foster a vibrant and inclusive culture where you can work with talented colleagues to create new solutions and have impact for colleagues, clients and communities.
• Our scale enables us to provide a range of career opportunities, as well as benefits and rewards to enhance your well-being.
• As of November 7, 2024, the Business Group Global Boilerplate Language, Country Specific Regulatory Language (Ex. US EEO Statement) OR Global Diversity Statement, and Global Hybrid Work Policy Statement have been automated except for:
• Marsh McLennan Agency
• Mercer Marsh Benefits
  
  

Oliver Wyman is a business of Marsh (NYSE: MRSH), a global leader in risk, reinsurance and capital, people and investments, and management consulting, advising clients in 130 countries. With annual revenue of over $27 billion and more than 95,000 colleagues, Marsh helps build the confidence to thrive through the power of perspective. For more information, visitoliverwyman.com, or follow us onLinkedInandX.

Marsh is committed to creating a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age, background, disability, ethnic origin, family duties, gender orientation or expression, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, or any other characteristic protected by applicable law.

Marsh is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one “anchor day” per week on which their full team will be together in person.

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