Data Modeler, Engineer 3
NBCUniversal
full-time
Posted on:
Location Type: Hybrid
Location: West Chester • Pennsylvania • United States
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About the role
- 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
- 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 and Apache Spark
- Contribute to standards for schema evolution, data contracts, and backward compatibility
- 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
- Support onboarding and adoption of data products by downstream consumers
- Embed data quality, consistency, and usability into data product designs
- Maintain clear documentation for data products, models, and metrics
- Support metadata, lineage, and discoverability initiatives aligned to data product governance
Requirements
- 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 understanding of semantic modeling and shared business metric design.
- Experience working in cloud‑native environments (AWS, Azure, or GCP).
- Ability to balance scalability, performance, quality, and usability in data product design.
- Excellent communication skills with the ability to explain complex data concepts to non‑technical audiences.
Benefits
- array of options
- expert guidance
- always-on tools
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
data modelinganalytics engineeringdata architectureschema designperformance optimizationdata transformationssemantic modelingdata qualitydata usabilitymetadata standards
Soft Skills
collaborationcommunicationsubject-matter expertiseproblem-solvingcross-functional teamworkdocumentationstakeholder engagementanalytical thinkingadaptabilityuser-centric design