Full-Time

Data Engineer / Senior Data Engineer

Data and Analytics

Updated on 8/2/2026

Marsh & McLennan

Marsh & McLennan

No salary listed

Gurugram, Haryana, India

Hybrid

Three days per week in the local office or at client sites are expected.

Category
Data & Analytics (1)
Required Skills
Scikit-learn
Kubernetes
Microsoft Azure
FastAPI
Python
Airflow
SAS
MySQL
TensorFlow
R
Apache Spark
SQL
Machine Learning
Postgres
RDBMS
ETL
Data Engineering
Docker
AWS
MongoDB
Flask
DevOps
Oracle
Databricks
Cassandra
Snowflake
Django
Google Cloud Platform
Requirements
  • A bachelor's or master's degree in Computer Science, Informatics, Data Science, or a related computational or quantitative discipline is required.
  • Experience designing and deploying cloud-native data applications is required.
  • Hands-on knowledge of test-driven development and continuous integration/continuous delivery pipeline integration is required.
  • Experience designing and deploying large-scale data solutions is required.
  • Fluency in Python is mandatory.
  • Experience with cloud platforms such as Amazon Web Services, Microsoft Azure, or Google Cloud Platform is required.
  • Strong SQL skills and experience with relational databases such as MySQL, PostgreSQL, or Oracle are required.
  • Familiarity with big data tools and frameworks such as PySpark, Databricks, Snowflake, and dbt is required.
  • Basic hands-on experience productizing data pipelines, building continuous integration/continuous delivery pipelines, and orchestrating code with tools such as Airflow and DevOps is required.
  • Familiarity with modern storage and computational frameworks is required.
  • Strong mentoring skills for guiding junior engineers on advanced data engineering concepts, platforms, and quality assurance processes are required for Senior and Lead levels.
  • Applicants must be willing to travel internationally as required.
  • Applicants must maintain confidentiality and data security.
Responsibilities
  • Work alongside Oliver Wyman consulting teams and partners and engage directly with clients to understand their business challenges.
  • Explore large-scale data and design, develop, and maintain data and software pipelines and extract, transform, and load processes for internal and external stakeholders.
  • Explain, refine, and develop the necessary architecture to guide stakeholders through model building.
  • Advocate best practices in data engineering, code hygiene, and code reviews.
  • Lead the development of proprietary data engineering assets, machine learning algorithms, and analytical tools across varied projects.
  • Create and maintain documentation for stakeholders and runbooks for operational excellence.
  • Work with partners and principals to shape proposals showcasing data engineering and analytics capabilities.
  • Travel to clients' locations across the globe when required, understand their problems, and deliver appropriate solutions collaboratively.
  • Keep up with emerging state-of-the-art data engineering techniques.
Desired Qualifications
  • Prior experience with compelling side projects or contributions to the open-source community.
  • Awareness of machine learning frameworks such as Scikit-Learn and TensorFlow.
  • Familiarity with containerization technologies such as Docker and Kubernetes.
  • Experience with backend web frameworks such as FastAPI, Flask, and Django.
  • Experience with NoSQL databases such as MongoDB or Cassandra.
  • R and SAS experience.

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