Oliver Wyman - Advanced Analytics Engineer - Mexico City

Reposted One Month Ago
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Paso, Rioverde, San Luis Potosí, MEX
In-Office
Junior
Professional Services • Consulting
The Role
Design, build, and optimize scalable data pipelines and models using Databricks, PySpark, and Python to support analytics, machine learning, and AI; integrate APIs, ensure data quality, enable batch and real-time processing, and contribute to CI/CD and DataOps practices.
Summary Generated by Built In
Company:Oliver Wyman

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.

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

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, visit oliverwyman.com, or follow us on LinkedIn and X. 

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.

Skills Required

  • 2+ years of experience in Data Engineering, Analytics Engineering, or related roles
  • Hands-on experience with Python
  • Hands-on experience with PySpark
  • Experience with Databricks
  • Strong SQL skills
  • Designing and developing scalable ETL/ELT pipelines and distributed data processing solutions
  • Experience working with structured, semi-structured, and unstructured data
  • Building and integrating APIs and enterprise data services
  • Supporting advanced analytics, AI, or machine learning initiatives
  • Understanding of modern lakehouse and cloud-based data architectures
  • Experience with workflow orchestration, automation, and CI/CD pipelines
  • Familiarity with cloud platforms (AWS, Azure, or GCP)
  • Experience with streaming and real-time processing technologies
  • Knowledge of MCP integrations and AI-driven workflow architectures
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The Company
HQ: New York, New York
9,026 Employees

What We Do

Oliver Wyman is a global leader in management consulting. With offices in more than 70 cities across 30 countries, Oliver Wyman combines deep industry knowledge with specialized expertise in strategy, operations, risk management, and organization transformation. The firm has more than 7,000 professionals around the world who work with clients to optimize their business, improve their operations and risk profile, and accelerate their organizational performance to seize the most attractive opportunities. Oliver Wyman is a business of Marsh McLennan [NYSE: MMC].

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