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Data Engineer

Endroit New York, États-Unis Type de Poste Temps plein Méthode de travail Hybride Niveau du poste Confirmé Référence de l'offre 12596 Entreprise Munich Re America Services Type d'emploi Régulier Domaine d'expertise Information Technology
Postuler

We’re adding to our diverse team of experts and are looking to hire those who are committed to building a culture that enables the creation of innovative solutions for our business units and clients.  We will consider a range of experience for this role and the offer will be commensurate with that.

The Company

As a member of Munich Re's US operations, we offer the financial strength and stability that comes with being part of the world's preeminent insurance and reinsurance brand. Our risk experts work together to assemble the right mix of products and services to help our clients stay competitive – from traditional reinsurance coverages, to niche and specialty reinsurance and insurance products.

Job Overview:

We are seeking a highly skilled Senior Data Engineer – DBX Platform (ML & Feature Engineering Focus) with a strong software engineering background to join our AI/ML Engineering GSI IT Team. In this role, you will be focused on building a DBX-based data platform that powers machine learning and advanced analytics. This role is ideal for someone who thrives at the intersection of data engineering, ML infrastructure, and software development, and is passionate about enabling scalable, production-grade feature engineering pipelines.

Key Responsibilities:

    • Build and optimize DBX ETL/ELT pipelines for feature extraction, transformation, and loading from structured and unstructured data sources.
    • Collaborate with ML engineers, data scientists, and software developers to deliver reliable, reusable, and versioned feature sets.
    • Implement CI/CD pipelines, testing frameworks, and observability for data workflows.
    • Develop feature stores, metadata tracking, and lineage tools to support data Ops.
    • Ensure data quality, governance, and compliance across all data assets.
    • Optimize performance and cost-efficiency of DBX clusters and jobs for data workloads.
    • Contribute to the architecture and design of the data platform and feature engineering framework.

Qualifications:

    • Strong proficiency in Python and relevant scripting languages, with experience in software development and scripting for DBX.
    • Expertise with  libraries and frameworks (e.g., Pandas, Numpy, Scikit-Learn, TensorFlow, PyTorch, DBX, MLFlow, dvc, dbt) and the ability to select the right tools for the use case.
    • Experience building inference endpoints (APIs) and managing compute architecture for efficient model inference and data handling.
    • Very good Azure and data & AI technology skills - specifically: DBX/ Python, Azure DBX Store, Azure AI Search.
    • Experience with DevOps practices, including Git, CI/CD using tools such as Azure Pipelines,  or similar.
    • Several years of experience in machine learning, data science, or a related field, with a strong understanding of statistics and data analysis.
    • Experience with Azure especially with data and ML services, containerization (Docker.

Preferred Qualifications:

    • Advanced Degree: Master’s degree in Computer Science, Engineering, Mathematics, with 5+ years of ML implementation experience or Ph.D. with 2+ years of hands-on ML Project experience.
    • Experience with Big Data: Strong proficiency with big data technologies such as Azure DBX and Spark.
    • Leadership Experience: Previous experience leading a team of data scientists or engineers.

Benefits:

    • Competitive employee benefits, including comprehensive health insurance, dental and sports coverage, and opportunities for certified training.
    • Flexibility in work arrangements, including home office options and flexible working hours.
    • A positive, team-oriented environment that fosters mutual trust, creativity, and initiative.
    • Opportunities for career growth within a global, innovative framework.
    • A diverse, multicultural workplace with a strong emphasis on team collaboration and professional development.

At Munich Re US, we see Diversity and Inclusion as a solution to the challenges and opportunities all around us. Our goal is to foster an inclusive culture and build a workforce that reflects the customers we serve and the communities in which we live and work. We strive to provide a workplace where all of our colleagues feel respected, valued and empowered to achieve their very best every day. We recruit and develop talent with a focus on providing our customers the most innovative products and services.

We are an equal opportunity employer. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

The Company is open to considering candidates in Princeton, NJ. The salary range posted below applies to the Company’s Princeton location.

The base salary range anticipated for this position is $104,200 - $152,800 plus opportunity for company bonus based upon a percentage of eligible pay.  In addition, the company makes available a variety of benefits to employees, including health insurance coverage, an employee wellness program, life and disability insurance, 401k match, retirement savings plan, paid holidays and paid time off (PTO). 

The salary estimate displayed represents the typical salary range for candidates hired in this position in Princeton. Factors that may be used to determine your actual salary include your specific skills, how many years of experience you have and comparison to other employees already in this role. Most candidates will start in the bottom half of the range. 

Postuler

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Primes liées à la performance de l'entreprise

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Nous soutenons votre bien-être financier à long terme grâce à des solutions de retraite conformes à la réglementation locale.

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Nous favorisons un environnement respectueux, inclusif et guidé par nos valeurs.

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Nous proposons des opportunités d'apprentissage sur mesure, axées principalement sur les compétences fondamentales et les connaissances essentielles à l'entreprise.

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