Data Architect Job Description for Resume

Updated on: May 10, 2022
Position Overview

Data architecture is the natural evolution from data analysis and database design and essentially reflects the emergence of Internet websites.

The need for integration of data from different database sources such as market feeds and news agencies is rife nowadays. And it is the job of a data architect to make sure that this is managed properly.

Typically, data architects are required to possess an end-to-end vision and to determine how a logical design will translate into set databases. The flow of data within an organization is decided by the data architect.

Position Requirements

To work as a data architect, one needs several skills including a sound background in data analysis, data migration tools, data modeling and integration, data warehousing, and database designs.

A degree in computer sciences is extremely important if you want to work in this position.

Usually, data architects are hired at this position if they have at least a few years of experience working in data architecture.

Other requirements to qualify for a data architect position include:

  • Dimensional data modeling proficiency
  • Understanding of structured analysis and physical database design
  • Experience with data profiling and quality tools
  • Large volume data processing knowledge

And much more…

Here is a list of job duties that are particular to the position of a data architect:

Sample Job Description for Data Architect Resume

• Identify business drivers, goals, and information in order to integrate them into the data architecture of the company.

• Design and build appropriate data structures to fit into the company structure.

• Provide consultation services and support to project leaders by providing them with assistance on data standards, naming conventions, and logical data designs.

• Develop and improve on data models and ensure that data integrity standards are met.

• Monitor and enforce compliance with data standards so that redundancies are minimized.

• Ensure the consistency and integration of existing data structures in the logical data model.

• Design and maintain metadata infrastructures and identify opportunities for data consolidation.

• Create and implement data warehouse and mart structures.

• Design and support the functioning of conceptual, logical, and physical data models.

• Perform data profiling and quality validation processes on each structure.

• Ensure the quality of systems by performing data analysis at various stages of the project.

• Work with developers to find creative and instant solutions to data problems.

• Evaluate data storage technologies and implement replication strategies to share data across multiple data centers.

• Work closely with data professionals to comprehend and support system changes.