Senior Data Analytics Engineer

Description

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.

Responsibilities:
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.

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