In the data engineering track, you will be primarily responsible for developing and monitoring high-performance applications that can rapidly deploy latest machine learning frameworks and other advanced analytical techniques at scale. This role requires you to be a proactive learner and quickly pick up new technologies, whenever required. Most of the projects require handling big data, so you will be required to work on related technologies extensively. You will work closely with other team members to support project delivery and ensure client satisfaction.

Your responsibilities will include

Working alongside Oliver Wyman consulting teams and partners, engaging directly with clients to understand their business challenges
Exploring large-scale data and designing, developing, and maintaining data/software pipelines, and ETL processes for internal and external stakeholders
Explaining, refining, and developing the necessary architecture to guide stakeholders through the journey of model building
Advocating application of best practices in data engineering, code hygiene, and code reviews
Leading the development of proprietary data engineering, assets, ML algorithms, and analytical tools on varied projects
Creating and maintaining documentation to support stakeholders and runbooks for operational excellence
Working with partners and principals to shape proposals that showcase our data engineering and analytics capabilities
Travelling to clients locations across the globe, when required, understanding their problems, and delivering appropriate solutions in collaboration with them
Keeping up with emerging state-of-the-art data engineering techniques in your domain

Your Attributes, Experience & Qualifications

Bachelors or master s degree in a computational or quantitative discipline from a top academic program (Computer Science, Informatics, Data Science, or related)
Strong mentoring skills, guiding junior engineers on advanced data engineering concepts, platforms, and quality assurance processes applicable for Senior and Lead levels.
Experience designing and deploying cloud-native data applications.
Hands-on knowledge of test-driven development (TDD) and CI/CD pipeline integration.
Pragmatic, methodical problem-solving approach with a focus on impactful delivery.
Ability to independently prioritize workload and meet deadlines in fast-paced environments.
Strong team collaboration skills combined with excellent verbal and written communication in English.
Willingness to travel internationally as required.
Strong respect for confidentiality and data security.

Technical Background

Prior experience in designing and deploying large-scale data solutions
Fluency in modern programming languages (Python is mandatory; R, SAS desired)

Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform
Strong SQL skills and experience with relational databases such as MySQL, PostgreSQL, or Oracle
Familiarity with big data tools and frameworks such as PySpark, Databricks, Snowflake, and DBT.
Basic hands-on experience with Data engineering tasks like productizing data pipelines, building CI/CD pipeline, code orchestration using tools like Airflow, DevOps etc
Familiarity with modern storage and computational frameworks
Valued but not required:
- Compelling side projects or contributions to the Open-Source community
- Awareness of machine learning frameworks (e.g., Scikit-Learn, TensorFlow)
- Familiarity with containerization technologies, such as Docker and Kubernetes
- Experience with backend web frameworks (FastAPI, Flask, Django) is beneficial
- Experience with NoSQL databases such as MongoDB or Cassandra

Data Engineer / Senior Data Engineer

Job Description

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