Description

Key Responsibilities

• Design scalable enterprise data models using dimensional modeling, conformed dimensions, certified facts, business keys, surrogate keys, and semantic ready structures
• Develop source to target mappings across raw, cleansed, refined, and curated data layers
• Define data ingestion patterns, business rules, transformation logic, and data quality standards
• Partner with Data Governance teams to establish ownership, lineage, metadata, privacy, retention, and access controls
• Collaborate with Data Engineering and Platform Engineering teams to implement scalable cloud solutions
• Partner with Technical Data Product Owners, analytics teams, and business stakeholders to develop reusable enterprise data products
• Participate in architecture reviews and contribute to enterprise standards and best practices
• Mentor engineers and analysts on dimensional modeling, medallion architecture, and enterprise data design

Technology Environment

• Snowflake
• Databricks
• Microsoft Azure
• Four layer medallion architecture
• Enterprise data products supporting analytics, reporting, semantic models, and AI initiatives

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, Data Architecture, or a related field
• Five or more years of experience in data architecture, data modeling, data engineering, or enterprise data platform design
• Strong hands on experience with dimensional modeling, including facts, dimensions, conformed dimensions, slowly changing dimensions, business keys, and surrogate keys
• Experience with medallion architecture, lakehouse architecture, enterprise data warehouses, and cloud data platforms
• Experience creating source to target mappings, profiling data, documenting business rules, and defining transformation requirements
• Strong SQL skills
• Experience with Snowflake, Databricks, Azure Data Factory, Azure Data Lake Storage, or similar technologies
• Experience with data modeling and metadata management tools such as ERwin, ER/Studio, or similar platforms
• Knowledge of batch, streaming, change data capture, API, incremental, merge, and historical load patterns
• Strong communication and stakeholder management skills

Preferred Qualifications

• Experience supporting retail, merchandising, loyalty, supply chain, finance, operations, or customer data domains
• Experience with Snowflake architecture, optimization, and governance
• Hands on experience with Databricks, Spark, PySpark, Delta Lake, and Unity Catalog
• Experience with semantic layer design and Power BI semantic models
• Experience with CI/CD, Git, Azure DevOps, Terraform, and infrastructure as code
• Experience working in Agile environments and enterprise data transformation initiatives
• Relevant certifications in Snowflake, Databricks, Azure, or Data Architecture

Key Skills

Education

Bachelor's or Master's degrees