Description

Design and implement scalable enterprise data models and cloud data platforms to support analytics, reporting, and AI initiatives.

This role is hybrid.

Responsibilities

• Design scalable enterprise data models using dimensional modeling, conformed dimensions, and semantic-ready structures.
• Define source-to-target mappings, data ingestion patterns, and transformation logic across raw, cleansed, and curated layers.
• Partner with Data Engineering and Platform teams to implement scalable cloud solutions in Azure.
• Collaborate with Data Governance teams to establish data ownership, lineage, metadata, and privacy controls.
• Mentor engineers and analysts on dimensional modeling, medallion architecture, and enterprise data design.

Required Skills

• 5+ years of experience in data architecture, data modeling, or enterprise data platform design.
• Strong hands-on experience with dimensional modeling (facts, dimensions, SCDs, business/surrogate keys).
• Experience with medallion/lakehouse architecture and cloud data platforms.
• Proficiency in Snowflake, Databricks, and Azure Data Factory.
• Strong SQL skills and experience creating source-to-target mappings and data profiling.
• Experience with data modeling and metadata management tools (e.g., ERwin, ER/Studio).
• Knowledge of batch, streaming, CDC, and incremental load patterns.

Preferred Skills

• Hands-on experience with Spark, PySpark, Delta Lake, and Unity Catalog.
• Experience with CI/CD, Git, Azure DevOps, Terraform, and infrastructure as code.
• Familiarity with semantic layer design, Power BI semantic models, or Agile environments.

Key Skills

Education

Bachelor's or Master's degrees