Description

Primary Responsibilities

• Build enterprise-wide canonical data models.
• Create conceptual, logical, and physical data models.
• Design real-time streaming architectures using Kafka.
• Define semantic models and data contracts.
• Work with business stakeholders and engineering teams.
• Build scalable cloud data architecture using AWS and Snowflake.
• Ensure governance, metadata, lineage, and data quality standards.
• Support AI/ML initiatives with well-designed data architecture.

Nice-to-Have Skills

• Apache Spark
• Delta Lake
• AWS EMR
• Enterprise Data Catalog tools (Collibra, Alation, Informatica EDC, etc.)
• AWS Certifications

Suitable Candidate Profile

This role is best suited for someone with:

• 10+ years in Data Architecture/Data Modeling
• Strong enterprise data modeling experience
• Kafka architecture expertise
• AWS cloud data engineering experience
• Snowflake implementation experience
• Knowledge of Data Mesh and Domain-Driven Design (DDD)
• Strong stakeholder communication skills

Keywords for Resume

To align your resume with this position, include keywords such as:

• Enterprise Data Architecture
• Canonical Data Model
• Data Mesh
• Semantic Data Modeling
• Conceptual Data Model
• Logical Data Model
• Physical Data Model
• Apache Kafka
• Event-Driven Architecture
• Schema Registry
• Event Streaming
• AWS S3
• AWS Glue
• Amazon Redshift
• AWS Lambda
• EMR
• Snowflake
• SQL
• Python
• ETL/ELT
• Data Governance
• Metadata Management
• Data Lineage
• Domain-Driven Design (DDD)
• Data Contracts
• AI/ML Data Foundation

Key Skills

Education

Bachelor's degree