Keller Postman LLC

Data Analyst

• Design, build, and maintain dynamic reports and dashboards to support leadership, Intake, and legal operations teams.
• Perform analyses to drive insights and improve client experience across the client journey.
• Develop predictive models to forecast case signup volume and staffing requirements to maintain optimal service levels.
• Conduct productivity analyses to evaluate Intake team performance and identify areas for operational improvement.
• Translate complex data into actionable insights to drive strategic planning and daily decision-making.
• Work with cross-functional teams to understand reporting needs and develop scalable solutions.
• Ensure accuracy, integrity, and reliability of data used in reports and analyses.
• Document data definitions, methodologies, and reporting standards to support consistency and clarity across the organization.
• Collaborate with data engineering and IT to enhance data sources and improve reporting infrastructure.
• Other duties as assigned.

Data Analyst, Intake

Data Engineer

• Develop, construct, test, and maintain data architectures, including databases and large-scale processing systems.
• Design, build, and optimize data pipelines and ETL/ELT processes leveraging Snowflake and Azure Services.
• Develop and maintain Snowflake data warehouses, ensuring efficient data modeling, partitioning, and performance tuning.
• Implement data flow processes that automate and streamline data collection, processing, and analysis.
• Ensure data governance, quality, and security best practices across all data platforms.
• Collaborate with analytics and business teams to improve data models that feed business intelligence tools.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability.
• Provide operational support for existing data infrastructure and develop new solutions as needed.
• Monitor, troubleshoot, and optimize system performance in Azure and Snowflake environments.
• Support CI/CD pipelines and automation for data workflows and deployments.
• Keep current with industry trends and innovations in data engineering and propose changes to the existing landscape.