Business Intelligence Engineer

Vericast•San Antonio, TX

1d•$90,000 - $109,000

About The Position

Responsible for the design, development, administration, and continuous improvement of enterprise contact center analytics, business intelligence, and AI-enabled reporting solutions. Owns the full analytics lifecycle, including data acquisition, integration, modeling, warehousing, reporting, dashboard development, trend analysis, forecasting, and insight generation. Works with Contact Center Operations, Business Intelligence, IT, Application Development, and external vendors to turn contact center and business-platform data into actionable insights supporting operational performance, customer experience, workforce optimization, financial reporting, and strategic decision-making. Serves as a technical and analytical leader 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. The role also exercises independent judgment in designing data models, reporting solutions, integrations, and analytics processes, and makes recommendations that inform analytics standards, platform improvements, and leadership decision support.

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 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 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 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 scripting and programming languages to automate data processing, integrations, and reporting workflows.
Experience with source control, DevOps, CI/CD pipelines, testing methodologies, and Agile development practices.
Proficiency in SQL development, query optimization, database performance tuning, SSAS development, DAX, MDX, semantic modeling, cube processing, and performance optimization.
Proficiency in database management, data warehousing, dimensional and semantic modeling, SSAS cubes, tabular models, 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.
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 including Power BI, Microsoft Fabric, SSRS, dashboards, data visualization, semantic models, and self-service analytics practices.
Understanding of software development lifecycle practices, source control, testing, CI/CD, and deployment management.
Ability to communicate complex technical information in clear, business-focused guidance to operational and executive stakeholders.

Responsibilities

Design, develop, and maintain SQL views, stored procedures, functions, database objects, data integrations, data warehouse structures, dimensional and semantic models, curated datasets, and analytical data assets.
Design and support ETL/ELT pipelines and monitor data quality, integrity, and consistency across reporting environments.
Partner with IT and application teams to identify and implement new data sources.
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.
Administer Power BI workspaces, gateways, security models, deployment pipelines, source control, testing, release management, and reporting governance.
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 reporting lifecycle management processes.
Analyze contact center operational, financial, workforce, and customer experience metrics; identify trends, anomalies, root causes, and process-improvement opportunities.
Develop forecasting models and support workforce planning; communicate findings and recommendations to operational leaders and executives.
Design and monitor key performance indicators 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, and research emerging AI, machine-learning, and analytics technologies for practical business applications.
Gather stakeholder requirements and translate business objectives into scalable reporting, data, and analytics solutions.
Present insights, recommendations, and reporting results to operational and executive leadership.
Participate in project planning, testing, user acceptance testing, and implementation activities; serve as a subject matter expert for contact center analytics and reporting.
Maintain documentation for reports, dashboards, datasets, KPIs, integrations, and data models; establish and enforce reporting standards and best practices; support audit and compliance activities related to reporting and data management.