Skill path
How to become a Database Architect
How to become a Database Architect: skill roadmap with 5 core skills, degree usually required, courses and salary data. Updated weekly.
Education & experience requirements
- Education
- Most of these occupations require a four-year bachelor's degree, but some do not.
- Experience
- A considerable amount of work-related skill, knowledge, or experience is needed for these occupations.
- On-the-job training
- Employees in these occupations usually need several years of work-related experience, on-the-job training, and/or vocational training.
Foundations
Skills assumed by employers — the base to build on
- Database design principlesFoundation
Guidelines for creating reliable databases. Employers need scalable and efficient data models. Learn through design courses and case studies.
- SQLFoundation
A language for managing and querying databases. Analysts and engineers use it to extract and analyze data from various sources.
- Data modelingFoundation
- Database management systemsFoundation
Software like MySQL or Oracle used to manage data. Employers need to maintain data infrastructure. Learn through vendor documentation and practice.
- Data warehousing conceptsFoundation
Methods for centralizing data for reporting. Employers need consolidated views for analysis. Learn through study of warehouse architectures.
Core skills
The skills that define the role today
- Data PipelinesHigh demand
Automated processes that move data between sources and destinations. Employers need reliable data flow for analytics. Learn by building simple pipelines with workflow tools.
- PythonHigh demand
A versatile programming language. Data professionals use it for analysis, automation, and building data-driven applications.
- Data ModelingHigh demand
Designing database structures to store data logically. Employers need efficient data storage and retrieval. Learn through design practice and study of schemas.
- SQLHigh demand
A language for managing and querying databases. Analysts and engineers use it to extract and analyze data from various sources.
- Data QualityHigh demand
Ensuring data is accurate and consistent. Employers need trustworthy data for decisions. Learn by profiling data and using validation techniques.
Tools in demand
Specific tools that appear in live postings
- HadoopIn demand
A framework for storing and processing large datasets across clusters. Employers need it to handle big data. Learn by setting up clusters and using its tools.
- Microsoft AzureIn demand
Microsoft's cloud computing services for building and running applications. Essential for cloud-based infrastructure. Learn through Azure documentation and free practice environments.
- SparkIn demand
An analytics engine for large-scale data processing. Employers need fast processing across systems. Learn through its documentation and hands-on projects.
- AWSIn demand
Amazon's cloud platform for computing, storage, and services. Employers use it for scalable infrastructure. Learn by experimenting with AWS free tier and following official documentation.