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Data Engineering Lead
Location:
US-NY-New York
Jobcode:
2495731
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We are seeking a highly skilled and motivated Lead Specialist - Data Engineering to join our dynamic team. This role will be in the New York City office.


Data Engineering Lead



What can you expect?

You will play a critical role in implementing the target data architecture for the organization.
You will be interacting with cross functional teams to implement the data framework, ensuring the highest quality, efficiency, reliability, security and availability of data while establishing consistent data standards, reference architectures, patterns, and practices across the organization
Project / Solution delivery


WHAT IS IN IT FOR YOU?

Become a key player in Guy Carpenters vision of revolutionizing its target architecture with the latest technologies.
A chance to gain valuable domain experience in large and dynamic insurance sector of the economy
A competitive compensation package, including excellent employee benefits.


WE WILL COUNT ON YOU TO:

Lead the data engineering to migrate our on premise data assets to the Azure cloud.
Lead the technology activities to enable the delivery of meaningful, data-driven capabilities in alignment with business strategies. Optimize data solutions ensuring scalability, security and performance
Develop, implement and deploy custom data pipelines using Azure Data Factory to support business intelligence dashboards, reporting and new data products.
Provide subject matter expertise in data acquisition and exploration leveraging Azure Databricks
Build best-in-class ETL/ELT-based solutions for effective data ingestion and transformation. Implement and manage DBT workflows to transform raw data into meaningful insights, ensuring data quality and consistency
Collaborate with stakeholders to design and implement scalable and maintainable data models. Ensure adherence to data governance and compliance standards in data modeling and architecture
Identify and address performance bottlenecks in data pipelines and queries. Implement strategies to optimize data processing and reduce latency in data delivery
Produce and be responsible for solution development and design documentation
Define development best practices and standards, and enforce through code reviews, automated testing and monitoring.


WHAT YOU NEED TO HAVE:

Bachelor's or Master's degree in Computer Science, Engineering or a related field.
10+ years in the data and analytics space with extensive experience delivering enhanced data and analytics capabilities
5 - 7+ years of hands-on experience designing and implementing data engineering solutions using Azure cloud offerings including Data Factory, ADLS, Azure Databricks, Azure Synapse.
Expertise and experience in modern data architecture patterns.
Expert in advanced SQL, preferrable using DBT or similar tools
3 - 5+ years' experience supporting PowerBI, QlikSense reporting
Experience migrating on-premises data, reporting and analytics assets such as Data Warehouses, BI tools, etc. to cloud technologies
Solid understanding of DevOps, Git integration, Code deployment using CI/CD pipelines, Experience building and maintaining CI/CD pipelines
Excellent problem-solving skills and the ability to troubleshoot complex data issues.
Strong communication skills and the ability to collaborate effectively with cross-functional teams.
3 - 5+ years Reinsurance or Insurance domain experience


What will make you stand out

Experience with AWS cloud platform
Python, Spark, JSON
Information and cloud security

Guy Carpenter & Company, LLC is a leading global risk and reinsurance specialist with more than 3,500 professionals in over 60 offices around the world. Guy Carpenter delivers a powerful combination of broking expertise, trusted strategic advisory services and industry-leading analytics to help clients adapt to emerging opportunities and achieve profitable growth. Guy Carpenter is a business of Marsh McLennan (NYSE: MMC), the worlds leading professional services firm in the areas of risk, strategy and people. The companys 85,000 colleagues advise clients in over 130 countries. With annualized revenue of over $23 billion, Marsh McLennan helps clients navigate an increasingly dynamic and complex environment through four market-leading companies including Marsh, Mercer and Oliver Wyman. For more information, visit (link removed) and follow us on LinkedIn and X.

Marsh McLennan 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, 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, veteran status (including protected veterans), or any other characteristic protected by applicable law. If you have a need that requires accommodation, please let us know by contacting (e-mail removed)

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.


The applicable base salary range for this role is $133,800 to $267,500.
The base pay offered will be determined on factors such as experience, skills, training, location, certifications, education, and any applicable minimum wage requirements. Decisions will be determined on a case-by-case basis. In addition to the base salary, this position may be eligible for performance-based incentives.

We are excited to offer a competitive total rewards package which includes health and welfare benefits, tuition assistance, 401K savings and other retirement programs as well as employee assistance programs.

Marsh McLennan

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