Data Engineer at Kimco Realty Corporation – Jericho, New York
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About This Position
Location: Jericho, NY
Full Time/Part Time: Full time
Req ID: R422-2026
Description:
******Unless specifically contracted, resumes from recruiting agencies are not being accepted for this position.*****
The Data Engineer will play a critical role in designing, building, and scaling Kimco’s enterprise data platform in the cloud. This role is responsible for developing modern data pipelines, enabling trusted analytics, and ensuring the reliability, security, and performance of cloud-based data solutions. While Kimco is a Microsoft-first organization (Azure/Microsoft Fabric), experience delivering comparable solutions on AWS and/or with Snowflake and/or Databricks is also valued. The role partners closely with business, analytics, and engineering teams to translate complex data requirements into scalable, future-proof architectures. This role will drive modernization initiatives, establish data engineering best practices, and mentor team members while continuously improving data quality, accessibility, and operational efficiency.
Key Responsibilities
Design, build, and maintain scalable, secure, and cost-efficient data solutions on a cloud data platform (Microsoft Azure/Microsoft Fabric preferred; AWS and comparable platforms considered).
Develop and optimize modern ETL/ELT pipelines supporting enterprise systems such as Salesforce, MRI, and other internal and external data sources.
Lead cloud data platform modernization and migration initiatives, reducing manual processes and improving data reliability.
Define and enforce data architecture, governance, security, and quality standards across the data ecosystem.
Partner closely with BI and analytics teams to enable trusted reporting and insights (e.g., Power BI and semantic models) across the organization.
Ensure high performance, availability, and cost efficiency through monitoring, performance tuning, and continuous optimization.
Translate complex business requirements into scalable, future-proof data architectures in collaboration with business and engineering stakeholders.
Support the development of training materials and conduct workshops for team members
Evaluate and adopt new data technologies and capabilities (e.g., Microsoft Fabric, Azure services, Snowflake, Databricks) to drive innovation and long-term platform scalability.
Contribute to the company’s purpose by improving the data platform and analytics capabilities that enable better decision-making and positive impact.
Travel up to 15%.
Qualifications
Required
Bachelor’s degree in computer science, Engineering, Information Systems, or equivalent practical experience.
5+ years of experience in data engineering, with at least 3+ years designing and delivering cloud-based data solutions (Azure preferred; AWS and other major cloud platforms considered).
Hands-on experience with modern cloud data engineering tools and services, such as Microsoft Fabric (Data Factory, Synapse), Azure Data Factory/Azure Synapse, Databricks, and/or Snowflake.
Proven expertise in building and optimizing large-scale ETL/ELT pipelines for high-volume, enterprise data environments.
Advanced SQL skills and experience with data modeling for analytics and reporting workloads.
Experience integrating data from enterprise systems such as Salesforce, ERP/property management platforms (e.g., MRI), or similar SaaS applications.
Solid understanding of data governance, security, data quality, and access control within cloud data platforms (Azure preferred).
Demonstrated ability to translate complex business requirements into scalable, production-grade data architectures.
Strong communication skills with the ability to collaborate effectively across business, analytics, and engineering teams.
Preferred
Cloud and data platform certifications (Azure preferred), such as DP-203 (Data Engineering on Microsoft Azure) or DP-600 (Microsoft certified: Fabric Analytics Engineer Associate) or equivalent AWS certifications, or Snowflake/Databricks credentials.
Hands-on experience with Power BI and enabling self-service analytics through a governed semantic layer (Microsoft Fabric experience a plus).
Familiarity with cloud cost optimization, performance tuning, and monitoring of data platforms at scale.
Experience with cloud data platform migrations and modernization initiatives.
Knowledge of CI/CD, infrastructure-as-code, and automated deployment patterns for data solutions.
Experience working in large-scale, enterprise or real estate / financial services data environments.
The expected salary range for this position is between $125,000 and $150,000. The actual compensation will be based on factors such as scope and responsibilities of the position, candidate's work experience, education/training, job-related skills, internal peer equity, market and business considerations and other factors permitted by law.
** Kimco Realty is an Equal Opportunity Employer – Veteran/Disability **
About Us: Kimco's mission is to create destinations for everyday living that inspire a sense of community and deliver value to our many stakeholders.
Kimco Realty® (NYSE: KIM) is a real estate investment trust (REIT) and leading owner and operator of high-quality, open-air, grocery-anchored shopping centers and mixed-use properties in the United States. The company’s portfolio is strategically concentrated in the first-ring suburbs of the top major metropolitan markets, including high-barrier-to-entry coastal markets and Sun Belt cities. Its tenant mix is focused on essential, necessity-based goods and services that drive multiple shopping trips per week.
Publicly traded on the NYSE since 1991 and included in the S&P 500 Index, the company has specialized in shopping center ownership, management, acquisitions, and value-enhancing redevelopment activities for more than 65 years. With a proven commitment to corporate responsibility, Kimco Realty is a recognized industry leader in this area. As of December 31, 2025, the company owned interests in 565 U.S. shopping centers and mixed-use assets comprising 100 million square feet of gross leasable space.