Business Data Architect/Modeler

• Overall experience – 10 Yrs

JD-

The Business Data Architect/Modeler will support enterprise data initiatives by designing and delivering scalable, modern data architecture solutions with a primary focus on canonical data modeling, semantic data mesh, and real‑time streaming architectures using Kafka. This role drives alignment across business domains and enables high‑quality, governed, and interoperable data for analytics and operational use cases.

Required Skills & Experience

• 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, Data Bricks (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 data models.
• Ensure consistent application of data governance, metadata management, and lineage standards across data domains.
• Architect and optimize data pipelines and storage solutions using Data Bricks, AWS (S3, Redshift, Glue, EMR, Lambda) and Snowflake.
• Contribute architectural artifacts, modeling standards, and reusable templates for enterprise data modeling.
• Support enterprise initiatives around real‑time data integration, semantic mesh, and AI/ML enablement through strong data architecture foundations.
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