Senior Principal Engineer - Data Engineering

Company:

Marsh Risk

Description:

We are seeking a talented individual to join our Data Engineer team at Risk Consulting. This role will be based in Pune. This is a hybrid role that has a requirement of working at least three days a week in the office.

Senior Principal Engineer - Data Engineer

This position is for an individual contributor in Data Engineer team at Marsh UK Analytics solutions who will develop and implement leading-edge techniques in artificial intelligence, machine learning, predictive modeling, and natural language processing as applied in commercial insurance and risk management. This position consults with senior colleagues on complex financial and statistical analyses, and develops approaches for new, market-leading tools.

We will count on you to:

• •Hands-onexpertisein Python, PySpark and other Data Engineering related packages.
• •Expertise in data management queries.
• •Build and maintain complex data pipelines through various data systems to drive optimization and implement business strategies.
• •Deploy API on the platform by understanding the technical ask
• •Hands-onexpertisein Databricks and its medallion architecture.
• •Develop statistical custom data models and algorithms from scratch to enhance current value proposition and new product development
• •Use advanced analytics to augment consulting deliverables with data backed outputs
• •Conduct research on theclient’srisk areas and prepare a point of view for consulting.

What you need to have:

• •Bachelor’s degree in engineering, Computer Science, Data Science, or related fields
• •4+ years of experience in the field of Data Engineering, Data Science, AIresearchor similar fields
• •Ability to develop strong internal/externalclient-orientedsolutions
• •Superior detail orientation, excellentcommunicationand interpersonal skills
• •Hands-onexpertisein modern programming languages such as Python, PySpark and SQL
• •Expertisein writing complex SQL queries.
• •Understanding Risk modelling and inferential statistics.
• •Knowledge of insurance contracts and risk business in general is a plus

What makes you stand out?

• •Understanding of insurance and risk management
• •Experience working with AI tools.
• •Experience of building data visualization in MS-excel, Power BI.

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 on 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 (NYSE: MRSH) is 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 marsh.com, or follow us on LinkedIn and X.

Marsh is committed to embracing a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age, background, caste, disability, ethnic origin, family duties, gender orientation or expression, gender reassignment, 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.