Real Estate Data Lead Analyst

Circle K•Charlotte, NC

About The Position

The Real Estate Data Lead Analyst reports to the Real Estate Strategy & Systems Senior Manager and serves as the primary owner of enterprise real estate data assets. The role develops a comprehensive understanding of where real estate data resides, how it is created and updated, which systems are authoritative sources of record, and how data flows across applications, integrations, databases, and analytical platforms. The position is the principal liaison among business and process owners, Enterprise Architecture, Data Engineering, application teams, implementation partners, and reporting teams, translating business needs into clear data requirements and ensuring trusted, governed, timely data is delivered as expected. The analyst stewards enterprise real estate data throughout its lifecycle, establishing business definitions, ownership, authorized use, documentation, quality, lineage, update cadence, and fitness for purpose. The role supports reliable delivery of data to authorized consumers and the enterprise real estate technology ecosystem, including Kalibrate, Mendix, Construction Management platform, SQL Server, Databricks, Snowflake, and related applications. It also supports implementations, integrations, migrations, system changes, and continuous improvement, including data profiling, cleansing, conversion, mapping, testing, reconciliation, acceptance, cutover, and production requirements. This role requires frequent computer and keyboard use, extended periods of sitting, and occasional standing, walking, bending, reaching, and lifting or moving items up to 35 pounds. Travel to store locations may be necessary. Work may involve tight deadlines and interruptions; the work environment is usually moderately noisy, with natural and fluorescent lighting. The position involves working with minimum direction and periodic supervision. Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions.

Requirements

Bachelor’s degree in Data Analytics, Information Systems, Computer Science, Business, Real Estate, or a related field.
Minimum of 3+ years of experience in data analysis, data management, business analysis, data governance, or a similar role supporting enterprise data environments.
Strong SQL proficiency, including querying, validating, reconciling, and troubleshooting data across enterprise databases and platforms.
Working knowledge of data governance, data quality, data lineage, metadata, data ownership, and source-of-record concepts.
Experience translating business and process needs into clear data requirements, definitions, mappings, and validation criteria.
Strong understanding of data integration and data flow concepts, including APIs, interfaces, pipelines, batch processes, and movement across systems.
Strong analytical, problem-solving, organizational, and communication skills, with excellent attention to detail.
Ability to work independently and collaboratively with business stakeholders, technical teams, vendors, and cross-functional partners.

Nice To Haves

Experience with enterprise data, analytics, and reporting platforms such as Databricks, Snowflake, SQL Server, Alteryx, Power BI, and related technologies.
Experience supporting data integrations, migrations, system implementations, testing, reconciliation, and production deployment.
Experience with enterprise data governance or data quality programs.
Experience with real estate, construction, development, or related business processes.
Experience with geospatial, real estate, or construction technology platforms such as Kalibrate and Mendix.
Experience working in an enterprise environment with Data Engineering, Enterprise Architecture, application, and reporting/analytics teams.
5+ years of relevant experience in data management, data analysis, business analysis, or a related field.

Responsibilities

Own and steward enterprise real estate data assets across the real estate lifecycle, ensuring business definitions, ownership, authorized use, documentation, quality, lineage, update cadence, and fitness for purpose.
Maintain an understanding of the real estate data landscape, including data origins, systems of record, data owners and stewards, critical data elements, dependencies, transformations, integrations, and data movement.
Partner with business and process owners to translate business needs, processes, and rules into data definitions, sources of record, data structures, transformation and integration requirements, delivery expectations, and reconciliation criteria.
Serve as the primary liaison among Real Estate stakeholders, Enterprise Architecture, Data Engineering, application teams, reporting and analytics teams, vendors, and implementation partners.
Establish and maintain data governance, quality, and documentation, including dictionaries, metadata, lineage, source-to-target mappings, critical data elements, validation rules, completeness and timeliness standards, stewardship responsibilities, access requirements, and reconciliation procedures.
Ensure data is available to authorized consumers in required timeframes and formats to support business processes, decisions, reporting, and analysis.
Work with Data Engineering and application teams to define and validate data pipelines, integrations, interfaces, APIs, batch processes, synchronization schedules, delivery mechanisms, and operational ownership.
Use SQL and enterprise data platforms to validate, reconcile, and troubleshoot data across SQL Server, Databricks, and Snowflake; develop and maintain appropriate queries, scripts, tables, views, and other approved data structures.
Support implementations, integrations, migrations, and system changes by defining and validating profiling, cleansing, conversion, source-to-target mapping, testing, reconciliation, acceptance, cutover, and production requirements, and coordinating with delivery teams.
Monitor and resolve data-quality and delivery issues by investigating discrepancies and root causes, coordinating remediation, and escalating material risks.
Support the enterprise real estate technology ecosystem and continuous improvement by ensuring data ownership, quality, integration, governance, delivery, and lifecycle expectations are defined and maintained.
Perform additional tasks as assigned.