Software Architect is responsible for the structural design and development of new software systems or extensive software revisions for external customers. Analyzes software requirements and defines system components to ensure efficient and scalable software architecture. Being a Software Architect designs and implements software solutions to consider business and technical needs and ensures compatibility with existing systems. Creates and maintains architecture documentation such as design specifications and diagrams to guide future maintenance and development. Additionally, Software Architect works with non-technical stakeholders to analyze requirements and understand constraints, dependencies, and business needs. Has in-depth knowledge of software development processes and methodologies. Requires a bachelor's degree. Typically reports to a manager. The Software Architect work is highly independent. May assume a team lead role for the work group. A specialist on complex technical and business matters. To be a Software Architect typically requires 7+ years of related experience. (Copyright 2024 Salary.com)
Job Title: Database Architect
Location: Kennesaw, GA(Onsite)
Duration: Long-term on W2
Required Skills:
have 10 years demonstrating a high degree of proficiency in designing and engineering complex, high-quality data technical architectures and detailed designs.
Five (5) or more years in a Data Architecture role architecting data warehouses and/or data lakes with big data technologies such as Hadoop, MapReduce, Hive, HBase, Redshift and BigQuery.
have depth and hands-on experience devising Architecture best practices, deliverables, drawings, and frameworks
have a record of accomplishment of crafting massively scalable, always-on, multi-region data systems.
can show a history of incrementally transitioning legacy data systems supporting modern, evolutionary architectures.
have utilized one or more cloud-based platforms such as AWS, Azure, and Google Cloud, and can elaborate on the *aaS hierarchy.
fluent in various forms of machine learning and have practical experience of how to deploy into applications.
understand the consequences of massively concurrent systems, and how to mitigate potential issues.
have proven expertise in a wide variety of database technologies, from PostgreSQL and SQL Server to NoSQL systems such as MongoDB, Couch, Cassandra, and/or Elasticsearch, and can explain their varied use cases.
have developed strategies for data movement, data obfuscation (data masking), record retention (Deletion and Archival), data infrastructure/security, operational data stores (ODS), enterprise data warehouses, data lakes and the operational reporting.
have deep knowledge of how to secure complex data systems and infrastructure against different attack vectors. You have led threat modeling exercises and helped craft remediation plans.
have been a decision maker in build vs buy scenarios, and how to break down the pros and cons of both.
have created systems spanning a variety of modern architectural paradigms.
have made the leap of guiding application teams to provide insights and actions through machine learning/artificial intelligence techniques.
Finance industry experience is a plus.