Data Engineer

Empire State Realty Trust•New York, NY

1d•Hybrid

About The Position

The Data Engineer will be responsible for designing, building, and supporting enterprise-wide AI and automation initiatives that improve and drive business efficiency, insight, and innovation. This role blends technical expertise in data engineering and AI integration, back-end development and automation with hands-on collaboration across business, analytics, and IT teams. Reporting to the Director of Application & Development, this position will support and enhance initiatives involving Informatica data pipelines, API integrations, Lakehouse data architecture, and AI-driven capabilities—including model deployment, virtual assistants, and workflow automation. This position works closely with business, analytics, and IT teams to deliver scalable, high-quality data and AI solutions across ESRT’s corporate and property operations.

Requirements

Strong proficiency in Informatica, SQL, Python, and Power BI
Experience with AI/ML frameworks, LLM-based tools, and cloud platforms (e.g., Azure, AWS, or GCP)
Hands-on experience developing and maintaining API integrations
Strong understanding of data governance, lineage, and security best practices
Excellent analytical, organizational, and communication skills
Ability to collaborate across teams and translate technical concepts into business value
Deep expertise in enterprise architecture, complex application design, AI integration, advanced analytics, and emerging technologies to deliver scalable, secure, and innovative solutions
Demonstrate deep, active listing to better understand another’s motivations, reality, and perspectives
Strong organizational skills: ability to prioritize work and meet deadlines in a fast-paced environment
Excellent written and verbal communication skills, adept at conveying complex technical concepts to diverse audiences and building trust with both technical and non-technical stakeholders
Dedication to refining development practices, adopting industry best practices, and driving sustainable organizational scalability
Development of SMART goals, followed by the timely execution of deliverables aligned with our IT roadmap which will be measure of employee and team success
Commitment to ethical, secure, and responsible data and AI practices
Bachelor’s degree in computer science, data engineering, data science, information systems, or related fields
5–8 years of experience in data integration, analytics, or related fields
5+ years of ticketing / attraction focused experience

Nice To Haves

Exposure to real estate, REIT, or property technology environments preferred

Responsibilities

AI AND AUTOMATION DEVELOPMENT: Design, build, and deploy AI-driven solutions using Python, APIs, and enterprise platforms (e.g., ChatGPT, Agentforce, internal automation tools, Agentic AI Assistance)
Partner with business and analytics teams to identify and prioritize automation opportunities that streamline workflows and enhance decision-making
Integrate AI capabilities into existing enterprise systems and applications to improve operational efficiency
DATA LAKE AND INFORMATICA MANAGEMENT: Develop, maintain, and optimize data pipeline, ETL workflows and integrations using Informatica, Azure Services, Microsoft Fabric, and Semantic Models for Power BI to ensure accurate, timely, and reliable data ingestion and transformation
Manage the enterprise Data Lake Architecture to support analytics, reporting, and AI model training, including ingestion, transformation, and overall data management
Uphold data governance standards, including lineage tracking, data quality, and documentation
Working knowledge of the Medallion Data Architecture
INTEGRATION ENGINEERING: Build and maintain integrations between applications, databases, and cloud platforms using APIs, middleware, and native connectors (e.g., REST/GraphQL API)
Optimize data flow between operational, analytical, and AI systems to ensure scalability, performance, and security
Collaborate with IT and application teams to standardize integration patterns and enforce governance
REPORTING AND ANALYTICS ENABLEMENT: Curate and publish high-quality datasets for analytics and visualization tools such as Power BI, including developing and maintaining semantic models and enterprise data schemas
Partner with business stakeholders to translate requirements into actionable data models and AI workflows
Enable self-service analytics and enhance business intelligence capabilities across the enterprise
GOVERNANCE, SECURITY, & DOCUMENTATION: Maintain clear and up-to-date documentation for technical specifications, data flows, integration architecture, and AI models
Enforce compliance with data security, access control, and governance frameworks
Implement monitoring and alerting for data quality, pipeline performance, and AI model accuracy
Adhere to Project Management Office (PMO) best practices
Support overall data governance, privacy, cybersecurity, and responsible AI practices