Data Modeling Engineer

Job Description

The Data Modeling Engineer builds dimensional models and Business Vault structures in Snowflake based on approved architectural designs and specifications. This SQL-first role applies approved business logic and KPI definitions to produce performant, documented, and governed data products that power BI, analytics, and AI use cases. The role partners closely with data engineering teams on upstream Data Vault inputs and with BI teams using Power BI to ensure accurate, reliable, and consumption-ready modeled data.

Architectural design decisions are provided; this role focuses on implementation and build execution within Snowflake.

Data Modeling Engineer
Department:
Data Architecture & Engineering

Reports To:

Director, Data Architecture & Engineering

Location:
Philadelphia, PA or Rockville, MD

• Build architect-approved star schemas and subject‑area dimensional models.
• Implement bridge tables resolve many‑to‑many relationships, hierarchies, and allocation logic prior to or within dimensional modeling.
• Apply established dimensional modeling patterns including surrogate keys, SCD Type 1/2, conformed dimensions, and approved bridge‑table techniques.
• Implement approved KPI definitions, filters, and business rules into governed semantic views.
• Deliver business‑friendly semantic layers optimized for Power BI consumption, standardizing metrics and hiding technical complexity.

• Apply Snowflake governance controls including data masking, sensitivity tagging, and (where applicable) row access policies.
• Ensure all modeled objects are documented using Snowflake comments and metadata standards.
• Validate modeled outputs for accuracy, completeness, and reconciliation to source‑of‑truth totals.
• Tune SQL for performance and cost efficiency, applying Snowflake best practices.
• Support SDLC and SOC 1 evidence requirements through clear documentation and controlled change processes.

• Support scheduled refreshes and dependencies using Snowflake‑native orchestration or approved tooling.
• Monitor modeled layers and resolve data, logic, or performance issues affecting downstream consumers.
• Partner with upstream teams to triage and resolve source data issues when needed.

• Partner with BI developers to ensure semantic layers answer business questions without additional tool‑side modeling.
• Collaborate with Data Engineers to align on grain, keys, freshness windows, and data contracts.
• Participate in sprint planning, estimation, and delivery ceremonies; communicate status and risks proactively.

• Use AI‑assisted development tools to accelerate SQL development, refactoring, optimization, and documentation.
• Maintain full accountability for correctness, governance, and semantic integrity of all AI‑assisted outputs.

• Strong hands on experience with Snowflake
• Familiarity and comfortability with Data Vault 2.0 methodology
• Advanced SQL expertise, including complex joins, window functions, and performance tuning.
• Strong understanding of dimensional modeling concepts including SCDs, surrogate keys, and conformed dimensions.
• Experience encoding business logic and KPI definitions into curated semantic views.
• Experience supporting semantic models and datasets consumed by Power BI and other BI tools.
• Familiarity with Snowflake governance features including data masking and sensitivity tagging.
• Experience supporting production data models through SDLC and incident resolution.
• Strong communication and documentation skills.

• Experience optimizing Snowflake performance and cost.
• Experience optimizing datasets for Power BI performance and usability.
• Exposure to BI and AI consumption patterns requiring clear semantics and business‑friendly metadata.
• Familiarity with Git‑based workflows and Azure Dev Ops.
• Experience contributing to a centralized semantic or data modeling function.

COMPENSATION:
The salary range for this position is $85,000 to $100,000. If both numbers are the same, that is the amount that Aramark expects to offer. This is Aramark’s good faith…