Description

You will design canonical, semantic, and enterprise-wide data models to enable cross-organizational interoperability and support data mesh principles.

This role is on-site.

Responsibilities

• Develop and maintain conceptual, logical, and physical data models aligned with business capabilities and modernization goals.
• Design real-time streaming architectures and event modeling strategies using Kafka, including schema management.
• Implement ETL/ELT patterns and data integration solutions leveraging AWS services (S3, Redshift, Glue, EMR, Lambda, EC2) and Snowflake.
• Partner with product owners and data engineering teams to translate business requirements into scalable data contracts.
• Apply data governance, quality, and lineage frameworks to ensure data integrity and discoverability.

Required Skills

• 9+ years of experience in data modeling, including canonical and semantic modeling.
• Deep proficiency in Kafka for event-driven architecture and real-time pipeline design.
• Strong SQL skills and hands-on experience with Python.
• Expertise with AWS data services (S3, Redshift, Glue, EMR, Lambda, EC2) and Snowflake.
• Proven track record with ETL/ELT design and distributed data systems.
• Experience with data governance, metadata, and lineage frameworks.
• Bachelor’s or Master’s degree in Computer Science, Information Systems, or related field.

Preferred Skills

• Experience with big data technologies such as Spark, EMR, or Delta Lake.
• Hands-on experience with enterprise data catalog and metadata systems.
• AWS certification (Solutions Architect or Data Analytics Specialty).

Key Skills

Education

Bachelor's or Master's degrees