Role Summary:
We are seeking an experienced Data Architect to design and implement our enterprise data architecture, with a focus on Data Warehouse/Data Lake / Data Mesh. This position offers an opportunity to shape the data foundation of our organization, working with cutting-edge technologies and solving complex data challenges in a collaborative environment.
Key Responsibilities:
- Design, develop, and maintain scalable enterprise data architecture incorporating data warehouse, data lake, and data mesh concepts
- Create and maintain data models, schemas, and mappings that support Reporting, business intelligence, analytics, and AI/ML initiatives
- Establish data integration patterns for batch and real-time processing using AWS services (Glue, DMS, Lambda), Redshift, Snowflake or Data Bricks.
- Define technical specifications for data storage, data processing, and data access patterns
- Develop data models and enforce data architecture standards, policies, and best practices
- Partner with business stakeholders to translate requirements into architectural solutions
- Lead data modernization initiatives, including legacy system migrations
- Create roadmaps for evolving data architecture to support future business needs
- Provide expert guidance on complex data problems and architectural decisions
Required Qualifications:
Education & Experience
- Bachelor's degree in computer science, Information Systems, or related field; Master's degree preferred
- 8+ years of experience in data architecture, database design, data modelling or related roles
- 5+ years of experience with cloud data platforms, particularly AWS data services
- 3+ years of experience architecting MPP database solutions (Redshift, Snowflake, etc.)
- Expert knowledge of data warehouse architecture and dimensional modelling
- Strong understanding of AWS data services ecosystem (Redshift, S3, Glue, DMS, Lambda)
- Experience with SQL Server and migration to cloud data platforms
- Proficiency in data modelling, entity relationship diagrams, and schema design
- Working knowledge of data integration patterns and technologies (ETL/ELT, CDC)
- Experience with one or more programming/scripting languages (Python, SQL, Shell)
- Familiarity with data lake architectures and technologies (Parquet, Delta Lake, Athena)
- Excellent verbal and written communication skills, with ability to translate complex technical concepts to varied audiences
- Strong stakeholder management and influencing skills
- Experience implementing data warehouse, data lake and data mesh architectures
- Good to have knowledge of machine learning workflows and feature engineering
- Understanding of regulatory requirements related to data (Fed Ramp, GDPR, CCPA, etc.)
