Description

Design scalable enterprise data models and define data ingestion patterns to support analytics and AI initiatives.

This role is on-site.

Responsibilities

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

Required Skills

• 5+ years of experience in data architecture, data modeling, or enterprise data platform design.
• Strong hands-on experience with dimensional modeling, including facts, dimensions, SCDs, and surrogate keys.
• Experience with medallion or lakehouse architecture and cloud data platforms.
• Proficiency in SQL and experience creating source-to-target mappings and data profiling.
• Experience with Snowflake, Databricks, and Azure Data Factory or similar technologies.
• Knowledge of batch, streaming, CDC, and historical load patterns.
• Experience with data modeling and metadata management tools (ERwin, ER/Studio).
• Bachelor's or Master's degree in Computer Science, IT, Data Engineering, or related field.

Preferred Skills

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

Key Skills

Education

Bachelor's or Master's degrees