Data modeling (dimensional, normalized, data vault)
Define and execute the enterprise data strategy across a multi-product SaaS portfolio, building scalable, secure, and analytics-ready AWS-native data platforms
Job Summary
Define and execute the enterprise data strategy across a multi-product SaaS portfolio, building scalable, secure, and analytics-ready AWS-native data platforms.
Establish architectural standards, design ingestion frameworks, pipelines, and data models, partnering with stakeholders to modernize systems and enable BI/AI use cases.
Togetherwork offers a comprehensive benefits program including medical, dental, vision, 401(k) match, flexible PTO, and paid parental leave.
Matching Summary
Define and execute the enterprise data strategy across a multi-product SaaS portfolio, building scalable, secure, and analytics-ready AWS-native data platforms.
Skills & Requirements
Must-have
AWS-native data platforms
Data ingestion frameworks and pipelines
Data modeling (dimensional, normalized, Data Vault)
ETL/ELT workflows
Data governance and security standards
Cloud-native data lake and warehouse architectures
Nice-to-have
Multi-product SaaS environments
Continuous improvement and collaboration
Customer-focused execution
Key Requirements
8+ years of experience in data engineering or data architecture
Proven experience designing and implementing enterprise-scale data platforms in AWS
Deep hands-on expertise with AWS data services
Advanced SQL skills and strong proficiency in Python
Experience with workflow orchestration tools
Experience optimizing distributed systems for performance and cost efficiency
Experience implementing CI/CD practices for data engineering workflows
Work Rights
Must have current, unrestricted authorization to work