LightBox · 5 hours ago
Digital Solutions - Data Engineer
United States
Full-time
Onsite
Mid Level
3+ years expLightBox is a leading provider of data and workflow solutions across commercial real estate and location intelligence. As a Digital Solutions Data Engineer, you will design and maintain geospatial data solutions, collaborate with a team of engineers, and ensure the delivery of high-quality data to support client engagements.
Commercial Real EstateSoftware
Responsibilities
Fulfill LightBox’s custom and recurring data deliveries to clients
Develop an in-depth understanding of LightBox data assets, infrastructure, and software platforms (e.g., LightBox Vision, SpatialStream)
Analyze business and technical use cases and propose data solutions aligned with business objectives
Assess client and internal requirements and design data and software solutions accordingly
Model and architect data to address complex business problems
Analyze and resolve technical data and application issues
Design, build, and maintain geospatial data layers from inception through production, including:
Data research and sourcing
Data acquisition and ingestion
Transformation and enrichment
Quality assurance and validation
Deployment and post-deployment support
Serve as a point of contact for external data vendors and data sources, investigating discrepancies, validating data availability and update cadence, and coordinating issue resolution to ensure data accuracy and reliability
Manage and evolve a portfolio of geospatial data layers focused on the disclosure risk market, ensuring accuracy, regulatory relevance, scalability, and long-term maintainability
Create and maintain automated data pipelines to prepare and manage datasets for specific use cases
Develop, test, and document ETL (extract, transform, load) processes to meet business and technical requirements
Develop data acceptance criteria, quality assurance plans, and automated testing routines
Investigate data-related issues and implement durable resolutions
Create tools and workflows to automate and optimize existing processes
Participate in structured knowledge transfer activities with existing team members, including reviewing legacy workflows, validating assumptions, documenting processes, and assuming ownership of data layers as responsibilities transition to other projects
Work closely with peers across Product, Engineering, Data, Sales, and Digital Solutions teams to align requirements, manage dependencies, and ensure successful delivery and adoption of data solutions
Own and maintain comprehensive documentation for each GIS data layer, including data sources, processing logic, QA criteria, deployment details, assumptions, and known limitations, to support reproducibility, cross-training, and long-term sustainability
Qualification
Required
Bachelor's degree or certificate in GIS, Geography, Computer Science, or a related discipline
Strong academic record with a solid foundation in GIS and Data Engineering
Familiarity with GIS standards, principles, best practices, open-source tools, and public domain data
3-5 years of experience as a GIS Analyst, Data Engineer, or Data Analyst (NOTE: qualified recent graduates will not be considered)
Outstanding organizational, communication, analytical, and interpersonal skills
Ability to quickly understand technical products and explain concepts to non-technical audiences
Experience with project management techniques like Agile and Scrum
Proven track record of meeting deadlines and managing multiple varied tasks
Fundamental knowledge in SQL (spatial), Python, ETL, and data management to aggregate, gather, manipulate, or validate data
Proficiency with GIS software packages and open-source tools (e.g., QGIS, ESRI, GRASS, GDAL, OGR)
Optimize geospatial data layers for performance and scalability, applying techniques such as geometry simplification, vertex thinning, indexing strategies, and efficient spatial transformations to support downstream applications and client delivery
Experience utilizing Python modules, packages, and libraries
Experience with pipeline orchestration technology (e.g., Prefect, AirFlow)
Proficiency with pipeline transformation tools, using Python and the Pandas library
Scripting experience
Ability to document workflows concisely
Commitment to exceeding assigned tasks and project expectations
Experience with cloud infrastructure (AWS), Git, Docker, Apigee, and Kubernetes
Has knowledge of data security best practices (when handling sensitive data)
Keen interest in data engineering with a 'tinkering' mindset
Excellent interpersonal, written, and oral communication skills
Driven to continually learn about and incorporate new technologies
Experience with implementing new technologies and continuous improvement of processes and workflows
Thrive in a self-driven environment
Understanding and integrating human and machine workflows
Team player with the ability to work collaboratively and take on new tasks
Reliable problem solver with the ability to work efficiently and independently
Embraces challenges with a positive attitude
Passion for learning new concepts and skills
Benefits
Competitive salary and benefits package
Company
LightBox
LightBox connects people, businesses, and data for deeper understanding
501-1000 employees
H1B Sponsorship
LightBox has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2021 (1)
Funding
Current Stage
Late StageLeadership Team
Eric Frank
Founder and Chief Executive Officer
Ron Frohock
SVP of Engineering - Data Platform
Recent News
2025-10-10
2025-09-12
Company data provided by crunchbase