An opportunity to shape a modern enterprise data ecosystem by designing scalable architectures across Data Warehouses, Data Lakes, and Data Mesh frameworks. This role focuses on building robust data foundations that power reporting, analytics, and AI/ML initiatives while solving complex data challenges using cutting-edge cloud technologies in a collaborative environment.
Key Responsibilities
- Design and implement scalable enterprise data architectures across data warehouse, data lake, and data mesh environments
- Develop and maintain data models, schemas, and mappings to support BI, analytics, and AI/ML use cases
- Establish batch and real-time data integration patterns using AWS services (Glue, DMS, Lambda) and platforms such as Redshift, Snowflake, or Databricks
- Define technical standards for data storage, processing, and access patterns
- Enforce architecture standards, governance policies, and best practices
- Translate business requirements into scalable architectural solutions
- Lead data modernization initiatives including legacy platform migrations
- Build data architecture roadmaps aligned with future business needs
- Provide expert guidance on complex data challenges and architectural decisions
Education & Experience
- Bachelor's degree in Computer Science, Information Systems, or related field (Master's preferred)
- 8+ years in data architecture, database design, or data modeling roles
- 5+ years working with cloud data platforms, particularly AWS data services
- 3+ years designing MPP database architectures (Redshift, Snowflake, etc.)
Technical Expertise
- Deep expertise in data warehouse architecture and dimensional modeling
- Strong knowledge of the AWS data ecosystem including Redshift, S3, Glue, DMS, and Lambda
- Experience with SQL Server and cloud migration strategies
- Advanced skills in data modeling, ER diagrams, and schema design
- Hands-on experience with ETL/ELT pipelines, CDC, and modern data integration patterns
- Proficiency in Python, SQL, or Shell scripting
- Familiarity with data lake technologies such as Parquet, Delta Lake, and Athena
Additional Strengths
- Ability to translate complex technical concepts for diverse stakeholders
- Strong stakeholder engagement and influence across technical and business teams
- Experience implementing data warehouse, data lake, and data mesh architectures
- Exposure to machine learning workflows and feature engineering
- Awareness of data governance and compliance frameworks (FedRAMP, GDPR, CCPA)
A role designed for professionals passionate about building scalable data ecosystems, modernizing platforms, and enabling data-driven innovation at scale.
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