Position Summary: 

The Analytics & AI Engineer designs, builds, and optimizes the data platforms, pipelines, and intelligent solutions that power reporting, advanced analytics, and AI-driven decision making across the organization. This role is responsible for the end-to-end engineering of analytics capabilities, from data ingestion and transformation to scalable architecture, automation, and AI integration. This role takes a builder and problem-solver who thinks in systems, pipelines, and reusable frameworks. They leverage modern data engineering practices to create reliable, scalable solutions while thoughtfully applying artificial intelligence and machine learning technologies to drive measurable business outcomes. This role serves as a key bridge between data, technology, and business stakeholders, enabling both current analytical needs and future AI innovation.

Essential Job Functions:

• Design, build, and maintain scalable data pipelines (ETL/ELT) that integrate operational, financial, and business data from multiple source systems.

• Architect, develop, and optimize data models, warehouses, and semantic layers that support enterprise reporting, self-service analytics, and Power BI/SQL-based solutions.

• Develop and maintain Python-based data workflows, automation processes, data quality frameworks, and monitoring systems that ensure reliability and performance.

• Identify, evaluate, and implement AI and machine learning solutions, including forecasting, anomaly detection, predictive analytics, and generative AI capabilities, where they create measurable business value.

• Build and support AI-enabled workflows, including large language model (LLM) integrations, intelligent document processing, data extraction, summarization, and conversational analytics capabilities.

• Establish and promote best practices for analytics and AI engineering, including documentation, testing, version control, data governance, CI/CD, and model lifecycle management.

• Partner with Data Science, Software Development, and business leaders to design scalable data architectures that support analytics, AI, and machine learning initiatives.

• Lead automation efforts that reduce manual processes, improve data quality, and increase operational efficiency across the organization.

• Evaluate emerging analytics and AI technologies, recommending solutions that improve business performance, scalability, and user experience.

• Serve as a technical subject matter expert for data infrastructure, analytics platforms, AI solutions, and the integration of new technologies and data sources.

• Collaborate with IT, Security, and business stakeholders to ensure data and AI solutions are secure, governed, compliant, and aligned with organizational standards.

• Support the development of data products and intelligent applications that enable business teams to make faster, more informed decisions.

• Other duties as assigned.

Minimum Qualifications/Skills:

• 3-5 years of experience in analytics engineering, data engineering, AI engineering, software engineering, or a related technical discipline; experience in multifamily, real estate, financial services, or similar industries is preferred.

• Strong proficiency in SQL and Python, with demonstrated experience building and maintaining scalable data pipelines, ETL/ELT processes, and analytical solutions.

• Experience designing data models, warehouses, and reporting architectures that support business intelligence and advanced analytics.

• Hands-on experience with cloud data platforms and services such as Azure, Snowflake, AWS, Databricks, or similar technologies.

• Familiarity with AI and machine learning tools, frameworks, and APIs, including predictive modeling, forecasting, LLMs, generative AI platforms, and automation technologies.

• Understanding of software engineering principles, including version control, testing, documentation, DevOps, and CI/CD practices.

• Strong analytical and problem-solving skills with the ability to independently design, implement, and optimize technical solutions.

• Ability to translate business requirements into scalable technical architecture and actionable insights.

• Strong communication and collaboration skills, with the ability to explain technical concepts to both technical and non-technical audiences.

• Curiosity, adaptability, and a passion for leveraging data and AI to solve complex business challenges and create measurable impact

Work Schedule: Monday-Friday (work schedule may vary depending on business needs).