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New

Data Engineer Sr

Munich Reinsurance America, Inc
United States, New Jersey, Princeton
Aug 01, 2025

Data Engineer Sr

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.




Company



Munich Re America Services



Location



Princeton
, United States

Job Overview:

We are seeking a highly skilled Senior Data Engineer - Databricks 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 Databricks-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 databricks 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 Databricks 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 Databricks.
  • Expertise with libraries and frameworks (e.g., Pandas, Numpy, Scikit-Learn, TensorFlow, PyTorch, Databricks, 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: Databricks / Python, Azure Datalake 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 Databricks 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.


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