Data Modeler (Engineer 3)

Make your mark at Comcast -- a Fortune 30 global media and technology company. From the connectivity and platforms we provide, to the content and experiences we create, we reach hundreds of millions of customers, viewers, and guests worldwide. Become part of our award-winning technology team that turns big ideas into cutting-edge products, platforms, and solutions that our customers love. We create space to innovate, and we recognize, reward, and invest in your ideas, while ensuring you can proudly bring your authentic self to the workplace. Join us. You’ll do the best work of your career right here at Comcast. (In most cases, Comcast prefers to have employees on-site collaborating unless the team has been designated as virtual due to the nature of their work. If a position is listed with both office locations and virtual offerings, Comcast may be willing to consider candidates who live greater than 100 miles from the office for the remote option.)

Job Summary

We are looking for an experienced Engineer III (Data Modeler) to help design and evolve data products that serve analytics, reporting, and operational use cases across the enterprise. This is a mid-to-senior level Individual Contributor role focused on modern data modeling, semantic design, and data architecture in a data product–oriented organization.

In this role, you will partner with product managers, data engineers, and analytics teams to define domain-aligned data products, translating business needs into scalable, well-governed data models built on cloud-native platforms such as Snowflake and Spark. The emphasis is on consumer-centric, reusable data assets, not traditional monolithic data warehouse development.

Job Description

This position is ineligible for visa sponsorship.  To be considered for this role, you must be legally authorized to work in the United States and not require sponsorship for employment now or in the future

Core Responsibilities

Data Product Modeling & Design

• Design and maintain conceptual, logical, and physical data models for domain-owned data products
• Translate product requirements into consumer-friendly analytical models, entities, and metrics
• Build domain-aligned, analytics-ready data structures optimized for modern access patterns
• Define and maintain semantic layers and shared business definitions across data products
• Apply modern modeling techniques (e.g., dimensional, denormalized, hybrid models) based on product use cases

Data Architecture & Platform Enablement

• Align data product models with modern data architecture patterns (lakehouse, multi-layered data platforms)
• Partner with data platform and engineering teams to ensure data products are efficiently implemented in:
• Snowflake (schemas, clustering, cost-aware design)
• Apache Spark (Spark SQL, schema design, performance-aware transformations)
• Contribute to standards for schema evolution, data contracts, and backward compatibility
• Balance scalability, performance, and cost in cloud-native environments

Product Collaboration & Ownership

• Work closely with data product managers, analytics engineers, and business stakeholders to refine product requirements
• Act as a modeling subject-matter expert within data product teams
• Review and guide data model and transformation designs across domains
• Support onboarding and adoption of data products by downstream consumers

Quality, Governance & Documentation

• Embed data quality, consistency, and usability into data product designs
• Maintain clear documentation for data products, models, and metrics
• Leverage modeling tools (e.g., Erwin and/or SAP PowerDesigner) to create and maintain enterprise and domain-level models
• Support metadata, lineage, and discoverability initiatives aligned to data product governance

Preferred Qualifications:

• 5+ years of experience in data modeling, analytics engineering, or data architecture roles.
• Strong proficiency in conceptual, logical, and physical data modeling techniques.
• Hands-on experience with Snowflake, including schema design, performance optimization, and cost governance.
• Experience developing data models and transformations in Apache Spark (Spark SQL, PySpark preferred).
• Familiarity with modern data architectures (e.g., lakehouse, domain-oriented data products, multi‑layered data platforms).
• Experience working with modeling tools such as Erwin or SAP PowerDesigner.
• Knowledge of schema evolution practices, data contracts, and metadata/lineage standards.
• Proven ability to collaborate with cross-functional data and business teams.
• Strong understandin