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
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
Build and maintain integrations between applications, databases, and cloud platforms using APIs, middleware, and native connectors (e.g., REST/GraphQL API)
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
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

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
Proven experience managing data pipelines, AI integrations, and enterprise analytics environments
Exposure to real estate, REIT, or property technology environments preferred
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
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
Commitment to ethical, secure, and responsible data and AI practices.

Data Engineer

Key skills