Jobs Companies Brookfield Properties Senior Data Engineer

Sobre esta vaga de Senior Data Engineer na Brookfield Properties

Brookfield Properties · Presencial · US NY - New York City

Company

Shared Services

Argo and Farm Family are specialty property and casualty insurance brands whose underwriting companies are wholly-owned subsidiaries of Clearbrook Holdings Inc. Argo and Farm Family partner with agents and brokers to provide insurance solutions that enable businesses to manage risks with confidence.


Job Description

AI-First Data Strategy for P&C Insurance Carrier | Lead Innovation in Property & Casualty Insurance Data Solutions

We are seeking a Senior Data Engineer to spearhead our transition to a modern, first, AI-first data strategy tailored to the unique demands of a property & casualty (P&C) insurance carrier.

Responsibilities

  • Lead the design and implementation of AI-powered data products and solutions that address business goals in underwriting, claims, risk management, and customer experience within the P&C insurance sector.
  • Define, develop, and register curated, reusable data products for lines of business such as auto, home, agriculture, commercial, and specialty insurance, enabling rapid insights and novel analytics across teams.
  • Collaborate with data analysts, data scientists, actuaries, underwriters, claims specialists, and business leaders to gather requirements and deliver scalable, secure, and reliable data solutions in compliance with insurance regulations.
  • Establish best practices for data engineering specific to P&C insurance, ensuring adherence to engineering excellence, data quality, governance, and privacy standards.
  • Mentor team members and foster a culture of innovation, continuous improvement, and cross-disciplinary collaboration.

Required Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
  • Extensive experience (5+ years) in data engineering, with proven expertise in technical development, data design, and implementation in the insurance industry, preferably within P&C.
  • Solid understanding of property & casualty insurance operations, including actuarial science, claims processing, underwriting, and pricing landscape.
  • Ability to multitask and manage competing priorities in a fast-paced, compliance-driven environment.
  • Experience implementing AI-first strategies and working with modern data platforms (e.g., Snowflake; Databricks, big data, analytics) relevant to P&C insurance.
  • Excellent communication and problem-solving skills, with the ability to translate complex business needs into actionable data solutions.

Preferred Skills

  • Experience with cloud-based data architectures commonly used in the P&C insurance industry (e.g., Snowflake, AWS).
  • Proficiency in Python, SQL, and industry-standard data engineering tools and frameworks.
  • Focuses on researching, building, and fine-tuning models from scratch or using frameworks.
  • Exposure with Generative AI, Large Language Models (LLMs), LangChain, and vector databases.
  • Experience with other advanced analytics approaches in property & casualty insurance for AI-centric products.
  • Knowledge of predictive modeling, telematics, geospatial analytics, and other advanced analytics applications in property & casualty insurance.

Join us to redefine how data empowers property & casualty insurance, accelerating speed to insight and enabling next-generation analytics and solutions powered by AI.

This is a 100% in-office position. Candidates must be able to work on-site at a designated company office during standard business hours.

The base salary range provided below is for hires in those geographic areas only and will be commensurate with candidate experience. Pay ranges for candidates in other locations may differ based on the cost of labor in that location. In addition to base salary, this position is eligible for an annual bonus based on company and individual performance as well as a generous benefits package.

  • Chicago Pay Range: $128,010 - $152,184
  • New York City Pay Range: $139,638 - $166,260
  • Omaha and Richmond Pay Range: $116,382 - $138,414

PLEASE NOTE: 

Applicants must be legally authorized to work in the United States. At this time, we are not able to sponsor or assume sponsorship of employment visas.


If you have a disability under the Americans with Disabilities Act or similar state or local law and you wish to discuss potential reasonable accommodations related to applying for employment with us, please contact our Benefits Department at 210-321-8400. 


Benefits and Compensation

We offer a competitive compensation package, performance-based incentives, and a comprehensive benefits program—including health, dental, vision, 401(k) with company match, paid time off, and professional development opportunities.


Core Values

At Clearbrook our Core Values are Integrity, Collaboration, Pursuit of Excellence and Forward Thinking. These values reflect who we are today and who we aspire to be - guiding how we work, how we lead and how we succeed.


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Como este salário de Data Engineer se compara

Esta vaga paga $140,097/yrem linha com da faixa típica para vagas de Data Engineer.

$101,500 a mediana $162,000 $242,500

Faixa típica $127,525–$195,875/yr, com base em 1,724 vagas de Data Engineer comparáveis na JobsRadar (pagamento anualizado em USD). Ver insights salariais de Data Engineer →

Sobre a Brookfield Properties

The Brookfield Real Estate ecosystem spans the globe through multiple operating companies, all united by our core values. We cover every facet of real estate—from offices and retail spaces to logistics centers, residential homes, and hotels. Across thousands of properties worldwide, we combine world-class expertise with deep local insights to drive exceptional value. Together, we transform neighborhoods and build lasting communities that stand the test of time. By leveraging the global scale of our operating companies and fostering trusted local partnerships, we collaborate seamlessly to support our communities and achieve shared success.

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