Oliver Wyman - Advanced Analytics Engineer - Mexico City
AI in this role
Company:
Oliver WymanDescription:
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, visit oliverwyman.com, or follow us on LinkedIn and X.
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. 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.
Key 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 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
Experience Required:
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
How we rate this
Oliver Wyman - Advanced Analytics Engineer - Mexico City at Marsh McLennan rates 68 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- What's a project where you used Databricks hands-on?
- Describe a typical day in a role like this one: which parts run through AI directly?
- If you removed AI from this role, what would be left, and how do you decide what still needs a human?
Adapt your resume
- List these exact terms on your resume: Databricks. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.
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