United States onlyWho We’re Looking For (Position Overview):
Spry Methods is on the search for a Data Architect to join our team supporting one of our government customers.
Team Information:
The Division has transformed to the Scaled Agile Framework (SAFe), applying lean and agile principles and practices. This team will utilize the SAFe methodology and principles to align and collaborate product delivery of Agile teams. The SAFe methodology defines the roles, artifacts, and processes for the required services. Utilizing SAFe, the team organizes and plans the operation and maintenance work to be completed in iterative cycles utilizing the knowledge and skills of the team to identify the priority of the work to be performed. Predetermined ceremonies are scheduled to assist with the planning.
The unit plays a crucial role in supporting the mission-critical systems and services provided to our law enforcement partners, ensuring that data-driven insights and technology solutions are reliable, secure, and readily available. As part of this mission, the unit continues to deliver common, scalable solutions across proprietary systems, leveraging secure Government cloud infrastructure to meet the high standards required for law enforcement data. By implementing standardized enterprise services within this cloud environment, the units goals are to streamline operations, reduce duplication, and improve efficiencies across the organization, ultimately fostering cost savings and better resource allocation.
What Your Day-To-Day Looks Like (Position Responsibilities):
- Participates in planning, definition, and high-level design of data solutions, exploring alternatives and evaluating new technologies.
- Develops and maintains scalable cloud-based data infrastructure, ensuring alignment with the organization's decentralized data management strategy.
- Designs and implements ETL pipelines using AWS services (e.g., S3, Redshift, Glue, Lake Formation, Lambda) to support data domain requirements and self-service analytics.
- Collaborates with data domain teams to design and deploy domain-specific data products, adhering to organizational standards for schema design, data transformations, and storage solutions.
- Establishes and enforces data governance practices, including compliance with data privacy, access controls, and lineage requirements, across the organization’s data assets.
- Maintains a comprehensive data catalog and governance tools, automating workflows to uphold data integrity and ensure discoverability across all domains.
- Leads the implementation and ongoing support of data mesh architecture, ensuring seamless integration and data flow across multiple domains.
- Ensures the availability and reliability of the organization’s Data Mesh software, managing operations and maintenance of the framework.
- Provides guidance and leadership on the cultural adoption of data mesh principles, including organizational training initiatives for data stewards and users.
- Communicates effectively with stakeholders to align technical data architecture with business goals, ensuring long-term support for analytics, insights, and innovation.
- Experience working in an Agile organization using Scrum, Kanban, Jira, Confluence, and SAFe.
What You Need to Succeed (Minimum Requirements):
- Secret Clearance Required
- Experience in Data Architecture: Minimum of eight (8) years of experience designing and implementing data architectures, including large-scale data environments such as data lakes, data warehouses, and data mesh frameworks.
- Experience with Cloud Platforms: Minimum of five (5) years of experience working with cloud-based data platforms (e.g., AWS, Azure, Google Cloud), particularly for data storage, processing, and analytics.
- Leadership and Team Management: Demonstrated two (2) years of experience leading and mentoring data engineering teams, fostering collaboration, and ensuring successful project execution.
- Education: A bachelor’s or master’s degree in computer science, Information Systems, Data Engineering, or a related technical field, preferred.
