Architect, Data & Analytics Engineering
Global Resource Center, United States
USD 148K-210K (estimate) Senior-level Full Time
Tasks
- Adopt data product operating model
- Apply dimensional modeling best practices
- Apply least privilege access controls
- Architect AI ML ready data pipelines
- Architect batch and streaming data pipelines
- Define data pipeline CI CD automated testing deployment
- Define data sharing standards APIs and external data products
- Define domain-driven data models
- Define enterprise data and AI platform architecture
- Design cloud-based data platform
- Design real time event driven data processing
- Enable data observability and monitoring
- Enable self service analytics with curated datasets
- Establish data documentation and usability standards
- Establish lakehouse architecture patterns
- Implement data governance frameworks
- Implement data quality lineage cataloging stewardship
- Implement semantic and metrics layer
- Lead root cause analysis for data quality issues
- Lead technology evaluations and proof of concepts
- Optimize cloud cost efficiency
- Optimize platform performance and reliability
- Partner in vendor and platform selection
- Provide guidance to stakeholders on data strategy
- Translate business needs into scalable data solutions
Perks/Benefits
- N/A
Skills/Tech-stack
APIs | AWS | Automated testing | Azure | BigQuery | CI/CD | DBT | Data Catalog | Data Governance | Data Lineage | Data Modeling | Data Observability | Data Processing | Data Quality | Databricks | Dimensional Modeling | Domain-Driven Design | Event Driven | Event-driven architecture | Feature Engineering | Generative AI | Google Cloud | LLM | Lakehouse | Machine Learning | Metrics layer | Monitoring | Normalized modeling | Predictive Analytics | Real Time | Real-time Data | Real-time Data Processing | SQL | Semantic layer | Snowflake
Education
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