5 Common Job Roles in Data Engineering

Job Role: Define data storage, integration, and management for enterprises. Responsibilities: Guide solution analysts, ensure integrated models, hands-on analysis. Prerequisites: Analytical skills, data modeling, database design, architectural understanding.

Data Architect

Job Role: – Design and implement ML algorithms, work with large datasets. Responsibilities: – Develop production-ready code, monitor data quality. Prerequisites: Python/R expertise, ML concepts, data mining, distributed computing.

ML Engineer

Job Role: Manage data warehouse back-end, ETL processes, dimensional design. Responsibilities: – Collaborate with data scientists, analysts, and engineers. Prerequisites: SQL Server, Azure DW, ETL experience, data accuracy.

Data Warehouse Engineer

Job Role:  Structure systems, improve business, analyze cost-benefit. Responsibilities:  Break down large projects, select IT products. Prerequisites: SQL, project management, software development experience.

Technical Architect

Job Role:   Define technical vision, solve business problems, ensure quality. Responsibilities:  Specify solutions, support build and operation, review architecture. Prerequisites: ITIL framework understanding, ECM knowledge, SDLC experience.

Solutions Architect

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