Business Intelligence Analyst Specialist
Job Location:
Austin, TX - USA
Monthly Salary:
Not Disclosed
Posted on:
6 days ago
Vacancies:
1 Vacancy
Job Summary
Position: Business Intelligence Analyst Specialist
Location: Austin TX 78751 (Onsite)
Duration: 12 months Contract with possibility to extension
The Specialist position is rarely selected and should only be considered after all other levels have been exhausted. The Specialist position is considered an expert position that has a comprehensive and authoritative knowledge of or unique skillset in a particular area. The Business Intelligence Analyst use data to figure out market and business trends for companies to increase profits and efficiency. They may work directly for a company or as a consultant. They able to look at large chunks of data and understand trends and then communicate those trends to the company.
10 or more years of experience relies on experience and judgment to plan and accomplish goals independently performs a variety of complicated tasks a wide degree of creativity and latitude is expected.
The Worker will serve as a technical lead and a critical liaison between technical IT and non-technical program staff working with complex technical data sources across the Clients departments and agencies. This role empowers Clients staff to effectively develop complex queries often using AI prompting techniques to access synthesize and report accurate data for official agency reporting and strategic decision-making. The ideal candidate has strong analytical skills a deep understanding of Clients programs and data strong history of BI/DW development and exceptional communication abilities to bridge the gap between technical data systems and operational users in the emerging context of AI.
Responsibilities:
- Strategic Liaison and Translation
- Work with program areas and project sponsor to gather business requirements and translate into technical specifications.
- Lead as technical project manager creating hybrid Agile sprint cycles epics and stories as well as Waterfall project plans and all project artifacts
- Act as the primary point of contact for program staff with data needs for federal state and internal reporting.
- Translate complex data requests and operational requirements into clear actionable queries for AI against complex analytics data sources.
- Explain technical findings and data limitations in simple non-technical language to end-users.
-
- AI Prompting and Data Synthesis
- Develop and refine effective AI prompts and query strategies to retrieve and synthesize data accurately from complex datasets.
- Guide non-technical users in crafting precise prompts to get the data they need ensuring fidelity and accuracy.
- Develop a library of standardized prompts and query templates for common reporting needs.
-
- Data Reporting and Visualization
- Extract integrate and analyze data from multiple complex internal and external sources to support HHS program needs.
- Collaborate with end-users and performance analysts or IT internal leaders to create and validate reports dashboards and data visualizations for program monitoring and official reporting.
- Provide subject matter expertise on validating output from AI particularly with respect to identifying and mitigating hallucinations.
- Ensure all data outputs adhere to agency reporting standards data governance and compliance regulations.
-
- Data Literacy and Training
- Champion data literacy across the organization by developing and conducting AI training sessions for non-technical staff.
- Create clear comprehensive documentation and tutorials on using AI tools for data synthesis.
- Promote a data-driven culture by enabling and empowering all employees to effectively utilize data and AI.
-
- Collaboration and Problem-Solving
- Work closely with data engineering IT and Program teams to troubleshoot data-related issues and address inconsistencies and mitigation strategies.
- Provide expert guidance to program staff on interpreting data trends and answering complex data questions.
- Stay up to date on new AI and data analytics tools and techniques to continuously improve data access data quality and reporting.
-
Candidate Skills and Qualifications:
10 - Required - Experience gathering business requirements and translating complex data requests and operational requireme nts into clear actionable queries for complex analytics data sources
10 - Required - Experience explaining technical findings and data limitations in simple non-technical language to end-users.
10 - Required - Experience in a complex data analysis senior business/systems analyst and/or data liaison role.
10 - Required - Strong experience with SQL for data extraction and manipulation.
10 - Required - Experience collaborating with end-users and performance analysts or IT internal leaders to create and validate reports dashboards and data visualizations for program monitoring and official reporting.
10 - Required - Excellent communication presentation and interpersonal skills.
10 - Required - Experience with data visualization tools such as Power BI and/or Tableau.
5 - Preferred - Experience leading as a technical project manager creating hybrid Agile sprint cycles epics and stories as well as Waterfall project plans and project artifacts
5 - Preferred - Experience with Business Intelligence/Data Warehouse
5 - Preferred - Experience acting as the primary point of contact for program staff with data needs for federal state and internal reporting.
5 - Preferred - Experience working in a health and human services or similarly regulated environment with a strong understanding of program data and reporting requirements.
5 - Preferred - Experience with data governance and data quality principles
2 - Preferred - Experience championing data literacy across the organization by developing and conducting training sessions for non-technical staff.
2 - Preferred - Experience training and mentoring staff with varying levels of data literacy.
1 - Preferred - Experience with creating AI prompt catalogs using tools such as Streamlit with Python.
1 - Preferred - Experience applying responsible AI practices and compliance with agency standards.
---