Senior Software Engineer - Semantic Modeling

This is a remote position; however, the candidate must reside within 30 miles of one of the following locations: Portland, ME; Boston, MA; Chicago, IL; San Francisco Bay Area, CA; and Seattle/WA.

About the Role/Team

The Semantic Data Modeling Layer is responsible for translating raw, domain-ingested data into structured, semantically meaningful, and trusted data entities that represent core business concepts.

As a Senior Software Engineer, you'll play a key role in designing , building, and scaling our semantic data layer that powers analytics, business intelligence, and data-driven decision-making across the organization. This role will be central to enabling a consistent, governed, and reusable definition of metrics, dimensions, and business logic that can be consumed across tools, platforms, and teams. Your work will be critical in creating a single source of truth, consolidating fragmented data sources into unified, reconciled views.

How you'll make an impact

• Build modular, reusable semantic definitions of business entities, metrics and hierarchies.

• Implement business rules, calculations, and aggregations in the semantic layer.

• Establish data governance principles to ensure consistency and metrics definitions are standardized and compliant.

• Define and implement robust data modeling solutions, ensuring data quality, consistency, and interoperability across the organization.

• Implement validation, testing, and monitoring of semantic models for accuracy and reliability.

• Partner closely with the data products team to understand business requirements and ensure semantic models align with their needs.

• Participate in code reviews, design sessions, and incident resolution-promoting high standards for code quality and operational reliability.

  Experience you'll bring

• 4-8 years of experience as a software or data engineer, ideally in high-volume or distributed systems environments.

• Strong programming skills in Python, Java, or another backend language for data services.

• Strong SQL skills and experience with modelling large-scale, complex datasets.

• Solid grasp of engineering fundamentals, including version control, modular design, testing, and performance tuning.

• Proven experience with at least one modern cloud data platform (Snowflake, BigQuery, Databricks)

• A collaborative mindset-comfortable working across domains, products, and infrastructure layers.

• A strong sense of ownership and accountability-you care deeply about building systems that last.