Description

• Significant experience with canonical data modeling and enterprise‑wide conceptual/logical/physical modeling.
• Strong background in semantic modeling and data mesh design principles.
• Hands‑on experience with Kafka, including event modeling, schema strategy, and real‑time pipeline architecture.
• Proficiency in AWS data services (S3, Redshift, Glue, EMR, Lambda, EC2) and Snowflake.
• Strong understanding of ETL/ELT design, data integration patterns, and distributed data systems.
• Familiarity with data governance, data quality, metadata, and lineage frameworks.
• Strong SQL skills and proficiency in at least one programming language (Python preferred).
• Excellent communication skills with the ability to work across technical and business teams.

Preferred Qualifications

• Experience with big data technologies (Spark, EMR, Delta, or similar).
• Hands‑on experience with enterprise data catalog and metadata systems.
• AWS certification (Solutions Architect, Data Analytics Specialty, etc.).
• Bachelor’s degree in computer science, Information Systems, or related field (Master’s preferred).

Key Responsibilities

• Develop and enhance canonical data models, semantic models, and domain‑driven data contracts to enable cross‑enterprise data interoperability.
• Produce conceptual, logical, and physical data models aligned to business capabilities, modernization goals, and data mesh principles.
• Design and implement data architecture patterns to support real‑time streaming solutions using Kafka.
• Partner with product owners, domain architects, and data engineering teams to translate business needs into scalable, well‑governed d

Key Skills

Education

Bachelor's or Master's degrees