Principal Architect & Data Engineer
Tasks
- Advise on cost variance detection and mitigation
- Align federated teams to enterprise architecture
- Architect RAG patterns and vector readiness
- Architect unified lakehouse architecture
- Build data governance contracts and quality frameworks
- Consolidate disparate storage and compute into lakehouse
- Define data trust standards and observability metrics
- Define lineage catalogs and access controls
- Define semantic modeling for AI and BI consumption
- Design data mesh and data zones
- Enforce data masking tokenization and policy as code
- Establish cloud cost attribution and storage tiering frameworks
- Implement security baselines including encryption and RBAC ABAC
- Map data products and ML models to business KPIs
- Mentor data architects and engineers
- Present architecture roadmaps and security risk assessments
- Scale agentic AI frameworks and registry
- Set standards for query analytics and data modeling
Perks/Benefits
- N/A
Skills/Tech-stack
ABAC | AWS | AWS Glue | Amazon Bedrock | Amazon Redshift | Amazon S3 | Apache Airflow | Apache Spark | BigQuery | CI/CD | Data Catalog | Data masking | Data mesh | Delta Lake | Encryption | Federated Query | Google Cloud | Iceberg | Infrastructure as Code | Lineage | Observability | PII Detection | PII Redaction | Policy-as-Code | Python | RAG | RBAC | SQL | Semantic layer | Terraform | Tokenization | Vector Databases | Vertex AI | “as-code”
Education
N/A
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