About the job
Join Salient CRGT as a Data Architect!
In this pivotal role, you will:
- Craft comprehensive data architecture strategies and propose solutions that align with business goals.
- Engage in all stages of data modeling, from initial concept to visualization and optimization of databases, including SQL development and database management.
- Assess business data requests, investigate data sources, and create detailed requirements documentation.
- Facilitate the design and development of new data sources, ensuring they integrate seamlessly with existing data warehouse structures.
- Architect extract, transform, and load (ETL) processes, analyze data logs for performance improvements, and enhance functionality.
- Establish monitoring mechanisms to guarantee data accuracy and integrity.
- Oversee the development of BI presentation layers.
- Design, develop, test, and deploy dashboards, scorecards, reports, and alerts that meet business user requirements while aligning with BI applications and warehouse structures.
- Generate support documentation for BI applications and provide user training and assistance.
- Lead the development of high-level conceptual and logical data models that support a comprehensive view of data requirements across systems.
- Manage the mapping of data sources, movement, interfaces, and analytics to ensure data quality.
- Create methods for tracking data quality, completeness, redundancy, and improvement.
- Conduct data capacity planning and feasibility studies.
- Collaborate with project managers and business leaders on all enterprise data-related initiatives.
- Identify and pursue opportunities for data reuse, migration, or retirement.
- Provide expert consultation during business requirements gathering sessions.
- Potentially collaborate with various departments to design and develop data marts.
- Lead the design, development, and implementation of data architecture for a data warehouse, including high-performance ETL tools and infrastructure.
- Conduct data profiling and quality analysis using SQL or other query tools.
- Develop solutions for data cleansing to eliminate errors and ensure consistency.
- Identify and leverage both internal and external data sources to bolster analytical capabilities.
- Reverse engineer data specifications from source systems through data discovery and analysis.

