Data Engineer

**Data Engineer**

We are seeking a Data Engineer to join our team at Oliver Wyman. This role will be based in Mexico City. As a Data Engineer at Oliver Wyman, you will play a key role in designing, developing, and maintaining our data infrastructure to support analytics and business intelligence initiatives.

**We will count on you to**:

- Design and implementation of processes to ingest data from various sources into the Databricks Lakehouse platform, ensuring alignment with architectural and engineering standards.
- Development, maintenance, and optimization of data models and ETL pipelines that support the Medallion Architecture (Bronze, Silver, Gold layers) to enhance data processing efficiency and facilitate data transformation.
- Utilize Databricks to integrate, consolidate, and cleanse data, ensuring accuracy and readiness for analysis, while leveraging Delta Lake for versioned data management.
- Implement and manage Unity Catalog for centralized data governance, ensuring proper data access, security, and compliance with organizational policies and regulations.
- Engage with clients and stakeholders to support architectural designs, address technical queries, and provide strategic guidance on utilizing the Databricks Lakehouse platform effectively.
- Stay updated on industry trends and emerging technologies in data engineering, particularly those related to Databricks, cloud data solutions, and ETL migration strategies, continuously enhancing your skills and knowledge.
- Promote available data and analytics capabilities to business stakeholders, educating them on how to effectively leverage these tools and the Medallion Architecture for their analytical needs.

**What you need to have**:

- 3 to 5 years of experience in technical data engineering roles with a large Corporate Enterprise Environment.
- Bachelor’s or master’s degree in computer science or equivalent
- Proficient in Pythonm SQL and experienced with enterprise database management and data warehousing technologies (e.g., Databricks, Redshift).
- Good Knowledge designing and developing automated data pipelines and workflows; familiarity with Git, CI/CD, or DevOps principles.
- Strong analytical, problem-solving, and communication skills, with the ability to translate complex technical concepts for diverse audiences.
- 2+ years of hands-on experience with cloud-based engineering technologies, including platforms like Databricks, AWS S3, Athena, Glue, or comparable enterprise cloud services.
- Advanced Level of English is a Must.

**What makes you stand out?**
- Proficiency in data visualization tools such as Power BI, Tableau, or equivalent.
- Experience in agile project delivery and collaborative team environments.
- Experience with containerization (Docker, Kubernetes) and orchestration tools like Apache Airflow

**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.

Marsh McLennan 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 McLennan 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 McLennan 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.