What are the responsibilities and job description for the Tableau Developer position at SRS Consulting Inc?
Role: Tableau Developer
Location: SFO, CA / Dallas, TX (Hybrid)
Duration: 12 Months
Job Description:
The project focuses on creating dashboards, reports, and monitoring solutions to help teams track the success of a new business initiative, improve data visibility, measure user adoption, and demonstrate business value.
Key Responsibilities
- Dashboard Development & Reporting
- Design and build interactive dashboards for different business users.
- Create dashboards that track:
- Data quality and system health
- User adoption and engagement
- Business outcomes and impact
- Enable users to analyze trends, compare performance across groups, and drill down into detailed information.
- Metrics & KPI Management
- Define, develop, and validate key business metrics and KPIs.
- Maintain clear documentation for all metrics and reporting logic.
- Ensure consistent measurement across teams.
- Data Integration & Modeling
- Connect and consolidate data from multiple sources.
- Design data models and transformations required for reporting.
- Ensure data accuracy, consistency, and governance compliance.
- User Experience & Stakeholder Support
- Develop dashboards tailored for different audiences, including leadership and operational teams.
- Ensure reports are easy to understand and drive actionable decisions.
- Gather feedback and continuously improve reporting solutions.
- Ongoing Support & Enhancements
- Maintain and enhance dashboards and reports.
- Fix data and reporting issues as they arise.
- Update metrics and reporting requirements as business needs evolve.
Expected Business Outcomes
- Real-time visibility into program performance and adoption.
- Early identification of risks, data issues, and operational gaps.
- Improved decision-making through data-driven insights.
- Clear measurement of business value and return on investment (ROI).
AI-Driven Data Operations (Agentic Data Ops)
The initiative also includes modernizing Data Operations processes by introducing AI-powered automation to reduce manual effort and improve efficiency.
Key Responsibilities
- Assess current data operations processes and identify automation opportunities.
- Design AI-driven workflows for:
- Data quality monitoring
- Anomaly detection
- Issue prioritization and triage
- Automated remediation recommendations
- Build and prototype intelligent automation solutions.
- Define operating models, governance processes, and best practices.
- Provide training, documentation, and knowledge transfer to internal teams.
Expected Outcomes
- Proactive identification and resolution of data issues.
- Reduced manual operational effort.
- Faster response to data quality problems.
- Scalable and intelligent data governance processes.
- Improved overall data reliability and business trust in data.