Business Intelligence Engineer

Vericast•San Antonio, TX

About The Position

The Business Intelligence Engineer designs, develops, administers, and continuously improves enterprise contact center analytics, business intelligence, and AI-enabled reporting solutions. The role owns the analytics lifecycle, including data acquisition, integration, modeling, warehousing, reporting, dashboard development, trend analysis, forecasting, and insight generation. It works with Contact Center Operations, Business Intelligence, IT, Application Development, and external vendors to turn contact center and business-platform data into actionable insights for operational performance, customer experience, workforce optimization, financial reporting, and strategic decision-making. The position provides technical and analytical leadership in modernizing reporting through automation, self-service analytics, semantic modeling, and emerging AI technologies, including Microsoft Copilot, Power BI AI capabilities, large language models, and enterprise AI solutions. Responsibilities span data engineering and integration; business intelligence and reporting; analytics, trend analysis, and insights; AI-enabled analytics and innovation; business partnership and project support; and governance and documentation. The role also exercises independent judgment when designing data models, integrations, reporting solutions, and analytics processes, and presents findings and recommendations to operational and executive stakeholders.

Requirements

Bachelor’s degree in Computer Science, Software Engineering, Information Systems, Data Science, or a related field; equivalent professional experience may be considered in lieu of a degree.
At least 3 years of experience in Business Intelligence, Data Engineering, Data Warehousing, Analytics Engineering, Software Development, or a related technical discipline.
At least 3 years of hands-on experience designing, developing, and supporting SQL Server databases, including views, stored procedures, functions, query optimization, performance tuning, and analytical data structures.
Experience designing, developing, and maintaining dimensional data models, star schemas, data warehouse structures, semantic models, curated reporting datasets, and SSAS Multidimensional Cubes and Tabular Models, including measures, KPIs, hierarchies, aggregations, partitions, processing strategies, and performance optimization.
Experience developing and supporting ETL/ELT processes, data pipelines, REST API integrations, and data transformation solutions using structured, semi-structured, and JSON-based sources.
Experience integrating and transforming data from multiple enterprise systems, cloud platforms, APIs, files, and third-party vendor solutions.
Experience building, administering, and supporting enterprise reporting solutions, dashboards, semantic models, and business intelligence platforms.
Experience gathering business requirements and translating them into scalable data, reporting, analytics, and self-service BI solutions.
Experience performing data validation, reconciliation, governance, and quality assurance across multiple systems and data sources.
Experience supporting operational reporting, KPI development, forecasting, trend analysis, and business performance measurement.
Experience with enterprise BI platforms such as Power BI, SSRS, Microsoft Fabric, Tableau, or similar technologies.
Experience with AI-assisted analytics, Microsoft Copilot, generative AI solutions, and semantic models supporting AI-enabled reporting and natural-language analytics.
Experience using Python, JavaScript, PowerShell, or similar programming or scripting languages to automate data processing, integrations, and reporting workflows.
Experience with source control, DevOps processes, CI/CD pipelines, testing methodologies, and Agile development practices.
Proficiency in SQL development and SQL Server Analysis Services (SSAS), including Multidimensional Cubes, Tabular Models, DAX, MDX, semantic modeling, cube processing, query optimization, and performance optimization.
Proficiency in database management, data warehousing, dimensional and semantic modeling, SSAS, and curated dataset development using SQL Server, Snowflake, Azure SQL, or similar technologies.
Experience designing, developing, and supporting ETL/ELT pipelines, data integrations, data movement processes, and enterprise data architectures across platforms.
Experience working with APIs, cloud platforms such as Azure, AWS, or GCP, enterprise applications, and structured and semi-structured data such as JSON, XML, and API payloads.
Proficiency with BI tools including Power BI, Microsoft Fabric, SSRS, semantic models, dashboards, data visualization, and self-service analytics practices.
Understanding of software development lifecycle practices, source control, testing, CI/CD processes, and deployment management.
Experience leveraging AI-enabled technologies, Microsoft Copilot, generative AI, large language models, and semantic models to enhance reporting, analytics, automation, and self-service data experiences.

Responsibilities

Design, develop, and maintain SQL views, stored procedures, functions, database objects, data warehouse structures, dimensional models, semantic models, curated datasets, and analytical data assets.
Build and support data integrations among platforms, APIs, enterprise data sources, cloud platforms, files, and third-party vendor solutions.
Design and support ETL/ELT pipelines for moving and transforming operational and reporting data; monitor data quality, integrity, and consistency.
Develop, administer, and support Power BI datasets, semantic models, dashboards, scorecards, executive reporting, and self-service analytics capabilities.
Establish reusable KPI frameworks, reporting standards, business rules, calculations, governed semantic models, and reporting governance processes.
Administer Power BI workspaces, gateways, security models, deployment pipelines, source control, testing, release management, and reporting lifecycle processes.
Develop monitoring, validation, reconciliation, and alerting solutions to support data quality, reporting accuracy, platform reliability, and performance standards.
Maintain reporting documentation, metadata, data dictionaries, and documentation for reports, dashboards, datasets, KPIs, integrations, and data models.
Analyze contact center operational, financial, workforce, and customer experience metrics, including volumes, service levels, abandonment rates, productivity, occupancy, callback utilization, queue performance, and operational efficiency.
Identify trends, anomalies, root causes, and process-improvement opportunities; develop forecasts and support workforce planning.
Communicate findings and recommendations to operational leaders and executive stakeholders, and design and monitor KPIs supporting business objectives.
Evaluate and implement AI-enabled analytics for reporting automation, insight generation, anomaly detection, and decision support.
Design datasets and semantic models for natural-language querying and AI-powered analytics; use Microsoft Copilot, Power BI AI capabilities, Microsoft Fabric, and approved enterprise AI platforms.
Identify opportunities to automate analytics processes; develop AI-assisted reporting templates, prompt libraries, and reusable insight-generation frameworks; support conversational analytics and natural-language reporting.
Research emerging AI, machine learning, and analytics technologies and recommend practical business applications.
Partner with stakeholders to gather requirements and translate business objectives into scalable data, reporting, analytics, and self-service BI solutions.
Participate in project planning, testing, user acceptance testing, and implementation activities; serve as a subject matter expert for contact center analytics and reporting.
Establish and enforce reporting standards and best practices, and support audit and compliance activities related to reporting and data management.