Role Summary
We are seeking a Data Architect to help design, build, and scale a modern Realty Data Platform on AWS and Databricks. This role will be responsible for developing data pipelines, integrating data from multiple internal and external sources, and creating trusted datasets that support analytics, reporting, and AI/ML-driven insights across the Real Estate organization. The ideal candidate combines strong hands-on data engineering skills with experience in cloud-native architectures, large-scale data processing, and modern lakehouse platforms.

Required Skills & Experience
Data Engineering
Strong experience building ETL/ELT pipelines.
Proficiency in Python, PySpark, and SQL.
Experience working with Apache Spark and distributed data processing frameworks.
Knowledge of data modelling, data quality, and data transformation techniques.
Databricks
Hands-on experience with the Databricks Lakehouse Platform.
Experience with Delta Lake, Databricks Workflows, and Unity Catalog.
Ability to develop, optimize, and troubleshoot Databricks notebooks and jobs.
AWS
Experience with AWS data services such as:
Amazon S3
AWS Glue
Lambda
IAM
Event-driven integrations and APIs
Understanding of cloud-native data architecture patterns.
Data Integration
Experience integrating data through REST APIs, JDBC connections, batch file transfers, or streaming mechanisms.
Familiarity with structured, semi-structured, and unstructured data formats including JSON, CSV, and Parquet.
AI/ML & Advanced Analytics
Experience preparing and engineering datasets for machine learning and AI workloads.
Understanding of AI/ML concepts, feature engineering, and model lifecycle processes.
Exposure to Databricks ML, MLflow, vector search, or Generative AI capabilities is a plus.
Ability to collaborate with business teams to identify opportunities for predictive analytics, trend analysis, document intelligence, and operational insights.

Senior Data Architect

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