Role Summary:

As Director of Data Analytics, you will be the first dedicated analytics engineering hire and are expected to help shape and grow the data function over time, responsible for building the foundations that power data-driven decision-making across the company. You will partner with teams across the business to design our data models, define core metrics, and make high-quality data easy to discover and trust.

You will formalize and scale a modern data stack, with Snowflake, dbt, and Sigma either in place or actively being implemented. Prior experience with every tool is not required; we are looking for someone who understands the underlying patterns and concepts of reliable data modeling, orchestration, testing, documentation, and self-service analytics.

In the first 12 months, you will help establish the core warehouse architecture, create trusted financial and property-level data marts, define key metrics in close partnership with Finance and Accounting, and support our ongoing ERP and Argus migrations by designing the data foundations and reporting needed before, during, and after implementation. The ideal candidate combines strong SQL, Python, and data modeling skills with hands-on experience translating business questions into reliable, well-documented data products. This is a highly collaborative, in-office role, with regular partnership across Finance, Accounting, IT, Leasing, Operations, and executive stakeholders.

Primary Duties and Responsibilities:

• Design and implement scalable data models and ELT pipelines that serve as the single source of truth for financial, operational, and property-level reporting
• Gain deep expertise in the company's data sources during key system migrations, including the transition from the current ERP to Yardi and from on-premise Argus Enterprise to Argus Cloud, and design models that abstract away source complexity for business users
• Integrate diverse data sources, including replicated application data, semi-structured cloud storage data, and file- or API-based sources, into the warehouse, working with IT and security to establish appropriate access, compliance, and ingestion guardrails for a public company
• Establish and maintain data governance practices across the warehouse, including row-level security in Snowflake, data classification, documentation, and auditability, coordinating with IT and security to establish access control policies
• Lead the maintenance, configuration, and ongoing improvement of data tooling across ingestion, transformation, orchestration, testing, documentation, and BI/semantic layers
• Work end-to-end on stakeholder requests: requirements gathering, solution design, implementation in the warehouse, documentation, and rollout to end users
• Support and enable business users by onboarding them to new data products, resolving data issues, and incorporating feedback into iterative improvements
• Define and maintain core metrics and KPI definitions (e.g., NOI, FFO, occupancy, leasing metrics, and operational KPIs) in partnership with business stakeholders

Qualifications and Skills:

• 7+ years of experience in analytics engineering, data engineering, or closely related roles, including ownership of production data models and pipelines
• Advanced SQL, Python, and command line skills and experience for data transformation, automation, integration work, and operationalizing managed data platform components, including scripted ingestion from file-based and API sources
• Hands-on experience with a cloud data warehouse/lakehouse (e.g., Snowflake, Databricks) and a structured transformation workflow (e.g., dbt)
• Hands-on experience with at least one major cloud platform (Azure, AWS, or GCP), including familiarity with core storage, compute, and other services relevant to data infrastructure (e.g., blob/object storage, IAM, networking basics, and working on cloud-hosted VMs for development and pipeline execution)
• Experience designing dimensional or star-schema models and building reusable, well-documented data marts that serve diverse business stakeholders across finance, operations, and other functions
• Hands-on experience operating modern data tooling across replication/CDC, orchestration, version control, testing, documentation, and BI/semantic layers; specific tools matter less than depth of ownership
• Demonstrated ability to partner directly with non-technical leaders to understand their goals, translate them into data requirements, and deliver practical solutions
• Strong communication skills, including the ability to clearly explain complex data concepts and trade-offs to executive and non-technical audiences

Preferred Qualifications:

• Exposure to financial reporting in a public company, REIT, real estate, or asset intensive business, especially familiarity with how accounting concepts and business rules translate into reporting metrics and data models
• Experience with modern Python data tooling for local development, exploratory analysis, and lightweight data apps, such as uv, Polars, DuckDB, marimo, Streamlit, etc.
• Familiarity with Yardi, Argus, or similar property or asset management systems

The starting annual cash compensation (base salary plus bonus) for this New Jersey based position is expected to be between $200,000 to $250,000. Actual salary will be determined based on skills, experience (to the extent relevant) and other job-related factors, consistent with applicable law.

Vornado Realty Trust is not offering relocation for this position based in Paramus, NJ.