Data Architect
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Key skills for this role
About the Role
Datamatics Technologies is seeking a Data Architect to design and implement scalable data platforms using Snowflake, SQL Server, and cloud-native services. The role involves data modeling, pipeline development, and performance optimization for enterprise data solutions.
Key Skills for This Role
Responsibilities
- Design, develop, and maintain conceptual, logical, and physical data models
- Implement and enforce data modeling standards
- Design Master & Reference Data Management strategies
- Implement Metadata Management and end to end Data Lineage
- Design Cloud & Hybrid Data Architecture and migration strategies
- Design and implement data platform solutions using Snowflake, SQL Server, and cloud native services
- Design and implement enterprise grade data pipelines using SSIS
- Orchestrate and monitor data workflows
- Tune performance of data workflows, SQL queries, and cloud services
- Define enterprise performance benchmarks, SLOs, and KPIs
Requirements
- 7 12 years of experience in data architecture and engineering
- Expertise in data modeling (conceptual, logical, physical)
- Experience with Snowflake, SQL Server, and cloud native services
- Proficiency in SSIS and data pipeline orchestration
- Knowledge of Master Data Management and Reference Data Management
Full Job Posting
Responsibilities
- Data Modeling: Design, Develop and maintain conceptual, logical, and physical data models for the data blueprints.
- Implement and enforce data modeling standards to ensure consistency and accuracy across the data stores and platforms.
- Design Master & Reference Data Management strategies.
- Implement Metadata Management and end to end Data Lineage.
- Act as Solution Architecture Review & Design Authority.
- Design Cloud & Hybrid Data Architecture and migration strategies.
- Data Platform Architecture & Engineering: Design and implement robust, scalable, and secure data platform solutions using Snowflake, SQL Server, and cloud native services.
- Collaborate with stakeholders to translate business and analytics needs into efficient data platform architecture.
- Define and implement data storage, access, and lifecycle management strategies across structured and semi structured data.
- Data Pipeline Development & Orchestration: Design and implement enterprise grade data pipelines utilizing Microsoft SSIS and proprietary integration platforms.
- Orchestrate and monitor data workflows, ensuring data reliability and availability.
- Implement fault tolerant, modular pipelines with robust logging and alerting mechanisms.
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