Kimco Realty

Kimco Realty

Data Engineer

Jericho, NY, USA · Senior

Sponsorship not specifiedDetected 177 days ago
SQLSnowflakeDatabricksAWSAzureCloud PlatformsCI/CDData EngineeringData VisualizationAccessibilitySalesforceERPCommunicationCollaboration

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Sponsors this role80
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70

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About the role

  • 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 expected salary range for this position is between $115,000 and $140,000.

Responsibilities

  • 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.
  • Partner closely with BI and analytics teams to enable trusted reporting and insights (e.g., Power BI and semantic models) across the organization.
  • 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.
  • 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).

Requirements

  • Bachelor's degree in computer science, Engineering, Information Systems, or equivalent practical experience.
  • 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.
  • 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.
  • Demonstrated ability to translate complex business requirements into scalable, production-grade data architectures.
  • 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.
  • 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).
  • Required
  • Proven expertise in building and optimizing large-scale ETL/ELT pipelines for high-volume, enterprise data environments.
  • 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.

Nice to have

  • 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).
  • AWS and comparable platforms considered).
  • Solid understanding of data governance, security, data quality, and access control within cloud data platforms (Azure preferred).
  • Hands-on experience with Power BI and enabling self-service analytics through a governed semantic layer (Microsoft Fabric experience a plus).

Compensation

  • The expected salary range for this position is between $115,000 and $140,000.
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This listing is sourced directly from Kimco Realty's careers page and normalized into a canonical job model.