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We are looking for a Senior Data Analytics Engineer to help shape and scale modern data capabilities for a real estate and property organization in Reston, Virginia. This role focuses on designing reliable data pipelines, structuring analytical datasets, and enabling high-quality reporting and advanced insights across the business. The ideal candidate brings strong engineering depth, practical analytics expertise, and the ability to turn business needs into well-architected data solutions.
Job Responsibility
Design, build, and maintain scalable data pipelines that ingest, transform, and deliver trusted datasets for analytics and operational use
Develop curated data layers using medallion-style architecture to improve data quality, accessibility, and consistency across the platform
Create and optimize dimensional models, including fact and dimension structures, to support reporting, trend analysis, and business intelligence needs
Use Python, PySpark, SparkSQL, and notebook-based development environments to engineer efficient data processing workflows
Partner with business and technical stakeholders to gather requirements and translate them into practical data products and analytics solutions
Apply data governance, security, and enterprise data management standards to protect information and support compliant data usage
Contribute to collaborative development practices through version control, code review, and shared engineering standards using Git
Support advanced analytics initiatives by preparing data foundations that can be used for machine learning and AI-driven use cases
Requirements
At least 5 years of experience in data engineering, analytics engineering, or a comparable data-centric role
Demonstrated expertise in dimensional modeling, including the design of fact tables, dimension tables, and slowly changing dimensions
Strong hands-on capability with Python, PySpark, SparkSQL, and notebook-based data development
Experience delivering end-to-end data solutions built on medallion architecture principles
Working knowledge of modern big data technologies such as Apache Spark, Hadoop, Kafka, and ETL frameworks
Familiarity with machine learning and AI concepts within contemporary analytics environments
Experience using Git within team-based software or data development workflows
Strong communication skills with the ability to align technical delivery with business objectives