Data Architect

First Command Financial Services, Inc.•Fort Worth, TX

9d•Hybrid

About The Position

First Command’s data architecture is the cornerstone of our comprehensive data strategy. We are on the lookout for a skilled Data Architect to enhance our business operations and elevate our customer experience by executing this strategy. The ideal candidate will design cutting-edge, cloud-based data solutions that adhere to the highest standards of quality, scalability, resilience, and security. In addition to data modeling, the role involves the creation and ongoing management of diagrams that map out data flow across the organization, as well as compiling comprehensive data source inventories. A collaborative approach is essential, as you will work closely with both business stakeholders and technology teams to comprehend their requirements and deliver tailored data solutions that are timely, accurate, and accessible to the appropriate parties.

Requirements

Minimum bachelor's degree required in computer science or relevant areas.
Master's degree or equivalent is preferred in computer science or relevant areas.
Minimum 7 years of relevant applied experience in data and analytics.
Minimum 2 years of applied experience in data architecture.
Relevant data certifications in cloud technologies are highly desirable.
Experience in Modern Data Architecture techniques and Cloud-based Data Technologies.
Proven experience in at least one of the modern ETL tools such as Data Factory, Matillion, dbt, etc.
Possesses experience in at least one of the contemporary databases technologies such as SQL Server, Oracle, DB2, etc.
Technology and personal leadership experience in architecting, modeling and successfully building highly scalable, secure, and resilient data solutions.
Experience in dimensional data modeling techniques to create a robust data platform for data analytics.
Proven experience in building different data models (entity, 3 NF, Data Vault, etc.) for application database design.
Experience in creating data flow diagrams and inventory of data sources.
Proven experience in Relational, Data warehouse, Master Data Management, reporting and analytical technologies.
Experience in working with cloud data services such as Data Lake, SQL, etc.
Strong knowledge in data analytics using any one of the cloud-based services such as Power BI, Tableau, Qlik, ThoughtSpot, etc.
Proficiency with DevOps principles and processes.
Solid knowledge in resource utilization and providing improvements for performance and cost optimization.

Nice To Haves

Experience in any NoSQL database is highly desirable.
Proficiency in CRM systems such as Salesforce, Dynamics 365, etc.
Knowledge in Data Science and Artificial Intelligence.
Knowledge in streaming or real-time analytics.
Experience in Agile methodologies (Scrum or SAFe frameworks).
Familiarity with scripting languages such as python, and/or git bash.
Financial services industry experience or other highly regulated industry experience.

Responsibilities

Working in synergy with business domain leaders, product owners/managers, enterprise architects, and key functional leads to provide superior data solutions.
Converting business needs into clear and intuitive conceptual and logical data models, ensuring they are accessible and comprehensible to all stakeholders.
Designing comprehensive data models to serve as the foundation for seamless and integrated data and analytics platform.
Developing sophisticated application database data models, crafting high-level enterprise data flow diagrams, and compiling a comprehensive inventory of data sources to enhance organizational data management.
Identifying and writing the technical enabler features to build solid foundation and improve overall performance.
Working in tandem with Data Governance to meticulously catalog and delineate data lineage, ensuring transparency and traceability across the organization.
Analyzing resource utilization within data solutions and proposing improvements to optimize efficiency.
Troubleshooting performance problems, tuning, and optimizing data solutions.
Understanding and adapting to changing business priorities and technological advancements.
Steering innovation and directing teams towards the implementation of forward-thinking solutions.
Building and maintaining systems and architectural documentation.
Suggesting enhancements for technical processes and procedures.
Assessing, creating prototypes, and endorsing new data technologies and platforms.