Business Intelligence Engineer

Vericast•San Antonio, TX

3h•$90,000 - $109,000

About The Position

The Business Intelligence Engineer is responsible for designing, developing, administering, and continuously improving enterprise contact center analytics, business intelligence, and AI-enabled reporting solutions. The role owns the analytics lifecycle, from data acquisition and integration through modeling, warehousing, reporting, dashboard development, trend analysis, forecasting, and insight generation. It partners with Contact Center Operations, Business Intelligence, IT, Application Development, and external vendors to turn contact center and business-platform data into insights supporting operational performance, customer experience, workforce optimization, financial reporting, and strategic decisions. The position provides technical and analytical leadership to modernize 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. Work includes building data integrations and pipelines; maintaining SQL Server and analytical data structures; developing and governing Power BI and other BI solutions; analyzing performance and forecasting trends; implementing AI-enabled analytics; consulting with business stakeholders; and maintaining reporting, data, and governance documentation. The role regularly communicates with operational and technical partners and external vendors, presents findings and recommendations to operational leaders and executives, and exercises independent judgment in designing analytics solutions and recommending data quality, reporting, automation, and platform improvements. Vericast describes its culture as collaborative, innovative, and focused on workplace flexibility.

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 formal degree.
At least 3 years of experience in Business Intelligence, Data Engineering, Data Warehousing, Analytics Engineering, Software Development, or related technical disciplines.
At least 3 years of hands-on experience designing, developing, and supporting SQL Server databases, including views, stored procedures, functions, query optimization, database performance tuning, and analytical data structures.
Experience designing and maintaining dimensional data models, star schemas, data warehouses, 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 data 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 for 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, SQL Server Analysis Services development, DAX, MDX, semantic modeling, cube processing, and performance optimization.
Proficiency in database management, data warehousing, dimensional and semantic modeling, SSAS cubes and tabular models, and curated dataset development using SQL Server, Snowflake, Azure SQL, or similar technologies.
Experience designing and supporting ETL/ELT pipelines, data integrations, data movement processes, and enterprise data architectures.
Experience working with APIs, cloud platforms such as Azure, AWS, or GCP, enterprise applications, and structured and semi-structured sources such as JSON, XML, and API payloads.
Proficiency with BI tools and practices including Power BI, Microsoft Fabric, SSRS, dashboards, data visualization, and self-service analytics.
Understanding of software development lifecycle practices, source control, testing, CI/CD, and deployment management.
Experience leveraging AI-enabled technologies, large language models, and semantic models to improve reporting, analytics, automation, and self-service data experiences.
Ability to communicate complex technical information clearly as business-focused guidance and to present analytical findings and recommendations to operational and executive stakeholders.
Ability to exercise independent judgment in designing data models, reporting solutions, integrations, and analytics processes and to evaluate data quality, reporting risks, automation opportunities, and emerging technologies.

Responsibilities

Design, develop, and maintain SQL views, stored procedures, functions, database objects, data integrations, data warehouse structures, dimensional and semantic models, and curated analytical datasets.
Build and support integrations across 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 and optimize SSAS Multidimensional Cubes and Tabular Models, including measures, hierarchies, aggregations, partitions, processing strategies, and performance.
Design, develop, administer, and support Power BI datasets, semantic models, dashboards, scorecards, executive reporting, and self-service analytics.
Develop reusable KPI frameworks, reporting standards, business rules, calculations, and governed semantic models for consistent enterprise reporting.
Administer Power BI workspaces, gateways, security models, deployment pipelines, source control, testing, release management, and reporting governance.
Develop monitoring, validation, reconciliation, and alerting solutions for data quality, reporting accuracy, platform reliability, and performance standards.
Maintain reporting documentation, metadata, data dictionaries, and reporting lifecycle processes.
Analyze contact center operational, financial, workforce, and customer experience metrics, including volumes, service levels, abandonment, 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 business-aligned KPIs.
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 through generative AI and workflow automation; 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 applications.
Gather stakeholder requirements and translate business objectives into scalable reporting, data, and analytics strategies.
Participate in project planning, testing, user acceptance testing, and implementation; serve as a subject matter expert for contact center analytics and reporting.
Maintain documentation for reports, dashboards, datasets, KPIs, integrations, and data models; establish reporting standards and support audits and compliance activities related to reporting and data management.