A Data Architect develops a common business vocabulary across the business enterprise, establishes strategy-driven data requirements, and draws out advanced integrated designs that align with these requirements.
This template contains the job description, requirements, and responsibilities for the Data Architect job. You can modify them to fit your organization's unique needs.
Data Architect Job Description
We are hiring Data Architects who are familiar with industry-acknowledged data architecture methodologies. So, proficiency in software architecture, network design, and implementation are highly commendable.
You should also a prior experience in handling digital data security, cloud, and automation technologies. Besides, statistical interpretation of data is highly appreciated.
What are we looking for?
- Advanced degrees in data science or applied mathematics (good to have)
- Expertise in relational database management system software
- Hands-on experience in agile methodologies, ERP implementation, Predictive modeling, NLP, etc
- Expertise in statistical modeling and analysis and database architecture
- Strong analytical capabilities using predictive analytics, data visualization tools
- Experience in using application server software and archival software
A Day in the Life of a Data Architect will look like this
- Design and develop data growth, analysis, and storage strategies for the company
- Support database requests in DB2, Teradata, Oracle, or SQL Servers
- Review SQL periodically for potential performance improvements and scope
- Guide data modeling efforts on storage technologies like HBase, Cassandra, etc
- Research and innovate with emerging open-source storage technology stacks
- Assist in ETL processes moving data through various DB platforms via custom-coded management applications
- Build and execute database applications using SQL Server Integration Services (SSIS)
- Create diagram deliverables through data modeling (conceptual, logical, and physical) for supported applications and projects
- Use ERWin to build logical data models from functional specifications, data requirements, and business rules provided by customers and clients
- Excellent understanding of data governance principles
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