Data Architect - Modern Enterprise Data Platform - Retail is Mandatory

Data Architect
- Modern Enterprise Data Platform
- Retail experience is Mandatory

• Contract

We provide Recruitment and Staffing services to many industries and domain through our innovative and customized solutions and passionate commitment to research. Ability to understand the hiring strategies, availability of talent and compensation benchmarking makes us proud hiring partner for various industries. We work as trusted business partners and always strive to deliver the most value and highest return on investment for our clients.

We are highly trained business professionals with strong understanding of clients need. We work closely with the leading staffing trade associations, training, and research organizations to ensure we are knowledgeable of thustry trends and technologies.

• Strong hands-on experience designing dimensional models, including facts, dimensions, conformed dimensions, grain definition, slowly changing dimensions, surrogate keys, business keys, and semantic-ready structures
• Practical experience with medallion architecture, lakehouse architecture, enterprise data warehouses, data lakes, and modern cloud data platforms
• Ability to analyze source systems, define source-to-target mappings, profile data, document business rules, and clarify ingestion, quality, and transformation requirements
• Experience with data modeling and metadata tools such as ERWIN, ER/Studio, or comparable platforms
• Clear communication skills with the ability to explain complex data architecture concepts in practical, business-relevant language

• Bachelors or masters degree in Computer Science, Information Technology, Data Engineering, Data Architecture, Engineering, or a related field.
• 5+ years of experience in data architecture, data modeling, data warehousing, data engineering, or enterprise data platform design.
• Strong hands-on experience designing dimensional models, including facts, dimensions, conformed dimensions, grain definition, slowly changing dimensions, surrogate keys, business keys, and semantic-ready structures.
• Practical experience with medallion architecture, lakehouse architecture, enterprise data warehouses, data lakes, and modern cloud data platforms.
• Ability to analyze source systems, define source-to-target mappings, profile data, document business rules, and clarify ingestion, quality, and transformation requirements.
• Strong SQL skills and the ability to review, interpret, and guide transformation logic across engineering and analytics teams.
• Experience with Snowflake, Databricks, Azure Data Factory, Azure Data Lake Storage, or comparable modern cloud data platform technologies.
• Experience with data modeling and metadata tools such as ERWIN, ER/Studio, or comparable platforms.
• Understanding of batch, streaming, CDC, API-based, file-based, incremental, merge, append-only, and historical load patterns.
• A collaborative style, strong judgment, and the ability to influence decisions across business, technical, governance, architecture, and engineering teams.
• Clear communication skills with the ability to explain complex data architecture concepts in practical, business-relevant language.

All your information will be kept confidential according to EEO guidelines.