Data Architect-Only W2

Ajna InfotechPhoenix, AZ
6hOnsite

About The Position

This individual will serve as a senior technical resource supporting a public-sector financial system, with a strong focus on data architecture, data engineering, and data integration. The role is hands-on and will support ongoing system enhancements, performance optimization, and the establishment of foundational data management practices. A. Data Engineering and Architecture Support Design, implement, and maintain relational data models supporting transactional and reporting use cases. Develop, optimize, and maintain SQL-based data objects, including tables, views, stored procedures, and indexes. Support data access and integration within a full-stack application environment. Design and implement data interfaces and services to support system integrations. Perform data performance tuning, diagnostics, and optimization activities. Support data validation, reconciliation, and auditability requirements. B. Application Enhancement and Delivery Support Support enhancement and feature development efforts for an existing production system. Participate in backlog refinement, technical design, and implementation activities related to data components. Provide production support and issue resolution related to data quality, performance, or integrity. Support testing, deployment, and post-release stabilization activities. C. Data Management Practice Enablement Assist in defining and documenting data management standards and best practices. Develop templates, patterns, and reference implementations to support consistent data engineering practices. Support the establishment of data governance and stewardship concepts appropriate to organizational maturity. Provide documentation and knowledge transfer to support long-term sustainability.

Requirements

  • Minimum of eight (8) years of hands-on experience in data engineering and/or data architecture roles.
  • Advanced proficiency with relational database platforms, including data modeling, query optimization, and performance tuning.
  • Experience supporting full-stack application environments, including integration with application code.
  • Experience designing and supporting data integrations and application programming interfaces (APIs).
  • Demonstrated experience supporting production financial or transactional systems.
  • Experience supporting post-implementation or post-go-live enhancement efforts.
  • Ability to operate independently as a senior technical resource with minimal supervision.
  • Experience working in public-sector or regulated environments.
  • Strong analytical, troubleshooting, and documentation skills.

Nice To Haves

  • Experience supporting public-sector financial, revenue, or accounting systems.
  • Experience with cloud or hybrid data architectures.
  • Familiarity with data governance, data quality, or master data concepts.
  • Experience working in agile or iterative delivery environments.

Responsibilities

  • Design, implement, and maintain relational data models supporting transactional and reporting use cases.
  • Develop, optimize, and maintain SQL-based data objects, including tables, views, stored procedures, and indexes.
  • Support data access and integration within a full-stack application environment.
  • Design and implement data interfaces and services to support system integrations.
  • Perform data performance tuning, diagnostics, and optimization activities.
  • Support data validation, reconciliation, and auditability requirements.
  • Support enhancement and feature development efforts for an existing production system.
  • Participate in backlog refinement, technical design, and implementation activities related to data components.
  • Provide production support and issue resolution related to data quality, performance, or integrity.
  • Support testing, deployment, and post-release stabilization activities.
  • Assist in defining and documenting data management standards and best practices.
  • Develop templates, patterns, and reference implementations to support consistent data engineering practices.
  • Support the establishment of data governance and stewardship concepts appropriate to organizational maturity.
  • Provide documentation and knowledge transfer to support long-term sustainability.
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