Summary
A publicly traded real estate company is looking for its first-ever Director of Data Analytics to build its data function from the ground up. This is a rare opportunity to shape the data strategy, tooling, and metrics for an entire organization from day one.
Company Information:
A growing, publicly traded real estate company known for its strong property portfolio and commitment to building a data-driven organization from the ground up.
Job Description:
- Build and maintain scalable data models and ELT pipelines serving as the source of truth for financial, operational, and property-level reporting
- Develop deep familiarity with data sources through ongoing system migrations, designing models that shield business users from source complexity
- Integrate data from replicated application sources, semi-structured cloud storage, and file/API-based feeds, partnering with IT and security on access and compliance standards
- Establish data governance practices including row-level security, data classification, documentation, and auditability
- Own selection, configuration, and improvement of data tooling across ingestion, transformation, orchestration, testing, documentation, and BI/semantic layers
- Manage stakeholder requests end-to-end, from requirements gathering through implementation and rollout
- Support business users in adopting new data products and troubleshooting issues
- Define and maintain core metrics and KPIs (NOI, FFO, occupancy, leasing/operational performance) in partnership with business stakeholders
Requirements / Qualifications:
- 7+ years in analytics engineering, data engineering, or a closely related field with hands-on ownership of production data models and pipelines
- Strong SQL, Python, and command-line skills for data transformation, automation, and integration
- Practical experience with a cloud data warehouse or lakehouse (Snowflake or Databricks) and a transformation framework (dbt)
- Experience with at least one major cloud platform (Azure, AWS, or GCP)
- Track record designing dimensional/star-schema models and building reusable data marts
- Hands-on experience across replication/CDC, orchestration, version control, testing, documentation, and BI/semantic layers
- Proven ability to translate non-technical stakeholder goals into data requirements
- Excellent communication skills with executive and non-technical audiences
