Senior Data & Integration Engineer Onsite | Denver, CO
$140,000$180,000 + Bonus | Full-Time | Exempt
A fast?growing nationwide real estate organization is seeking a Senior Data & Integration Engineer to build and own the data infrastructure that powers its expanding technology ecosystem. This is a full-time, onsite role (MondayFriday) working directly with the CTO in a high?velocity environment where every engineer leverages AI tools as part of their daily workflow.
We care about what you can do and what you've shipped, not where you learned to do it. About the Role
This role is responsible for creating the centralized data foundation that connects internal systems, external vendors, financial models, and AI-driven document pipelines into a single source of truth. Youll integrate operational systems, market data providers, and internal analytics to build a robust, scalable data layer that supports all applications across the organization.
Youll build data pipelines across three levels of complexity:
1. Pre?Built Connectors (Low Complexity)
Use platform connectors to integrate systems such as property management platforms, market data sources, and credit/risk data feeds. Work involves configuration, mapping, validationnot writing custom connectors.
2. Structured Uploads (Medium Complexity)
Handle ingestion of financial models, deal trackers, and construction budgets via Excel/CSV. Define templates, manage SFTP delivery, and configure validation workflows.
Build pipelines for PDFsincluding OMs, leases, rent rolls, and insurance certificatesusing AI-based extraction, validation, and ingestion into the unified data layer.
This is an infrastructure-first role, not a dashboarding position. Your work enables:
Real-time data delivery to internal applications
AI tools to generate investment analyses
Deal scoring and market comparison tools
Automated variance detection between underwriting assumptions and real performance
Youll collaborate across teams and have direct access to leadership, making communication skills and a team-first mentality essential. What Youll Do
Learn the unified real estate data platform, its data model, GraphQL API, and integration modules
Configure pipelines from operational systems, mapping source schemas into standardized property, lease, tenant, unit, and financial models
Integrate underwriting and DCF data; build variance comparisons between assumptions and actual performance
Deploy and manage AI-driven document extraction pipelines for complex PDF documents
Onboard market data sources (comps, credit data, climate/hazard data) using platform connectors
Build custom ingestion pipelines for semi-structured data via SFTP
Redirect internal applications to read from the centralized data layer
Set up monitoring, alerting, and automated data-quality checks
Extend the data model to support new business needs
Lead the organizations maturity from manual ingestion to fully automated workflows
Ongoing Responsibilities
Monitor, debug, and maintain pipelines across all systems
Handle schema changes from both source systems and the centralized data platform
Onboard new data sources as the organization grows
Manage and extend the API layer serving data to internal applications
Implement caching and fallback logic for resilience
Maintain documentation for pipelines, integration patterns, and data models
Stand up and maintain vector databases for semantic search across documents and investment materials
Improve sync frequency, monitoring coverage, and data quality across all sources
You May Be a Good Fit If You
Bachelor's Degree in Computer Science required.
Have 3+ years of experience building production data pipelines integrating enterprise systems
Are proficient in Python and SQL (PostgreSQL preferred)
Have experience with REST and GraphQL APIs
Have built ETL/ELT pipelines using Airflow, Dagster, Prefect, dbt, etc.
Treat data quality, validation, and monitoring as core engineering responsibilities
Use AI coding tools (Claude, Cursor, Copilot, etc.) as part of your daily workflow
Can take ambiguous integration requirements and deliver reliable solutions
Write clear documentation and communicate effectively with both technical and non-technical teams
Bring a positive, collaborative attitude
Bonus Points
Experience with real estate systems or market data providers
Experience with unified data aggregation platforms
Familiarity with vector databases (pgvector, Pinecone, Weaviate)
Background in real estate, financial services, or proptech data engineering
Experience with distributed compute (Spark, Flink) or cloud data warehouses (BigQuery, Snowflake, Redshift)
Experience building document-extraction or OCR pipelines
Experience designing or consuming GraphQL APIs
What We Dont Require
FAANG experience
Prior real estate knowledge (youll learn quickly; the models are intuitive once seen)
Applicants must be legally authorized to work in the United States. Sponsorship is not available for this position.