Business Intelligence Engineer

Vericast•San Antonio, TX

1d•Hybrid

About The Position

Responsible for the design, development, administration, and continuous improvement of enterprise contact center analytics, business intelligence, and AI-enabled reporting solutions. This role owns the full analytics lifecycle, including data acquisition, integration, modeling, warehousing, reporting, dashboard development, trend analysis, forecasting, and insight generation. The position works closely with Contact Center Operations, Business Intelligence, IT, Application Development, and external vendors to transform data from the contact center and business platforms into actionable insights that support operational performance, customer experience, workforce optimization, financial reporting, and strategic decision-making. This role serves as a technical and analytical leader responsible for modernizing reporting capabilities through automation, self-service analytics, semantic modeling, and emerging AI technologies including Microsoft Copilot, Power BI AI capabilities, Large Language Models (LLMs), and enterprise AI solutions.

Requirements

Bachelor’s degree in Computer Science, Software Engineering, Information Systems, Data Science or related field required. Equivalent professional experience may be considered in lieu of a formal degree.
3+ years of experience in Business Intelligence, Data Engineering, Data Warehousing, Analytics Engineering, Software Development, or related technical disciplines.
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, developing, and maintaining dimensional data models, star schemas, data warehouse structures, semantic models, curated reporting datasets, and SQL Server Analysis Services (SSAS) Multidimensional Cubes and Tabular Models, including measure development, 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 utilizing 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 activities across multiple systems and data sources.
Experience supporting operational reporting, KPI development, forecasting, trend analysis, and business performance measurement.
Experience with enterprise business intelligence platforms including 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 utilizing Python, JavaScript, PowerShell, or similar scripting/programming 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 including views, stored procedures, functions, query optimization, database performance tuning, and SQL Server Analysis Services (SSAS) development including Multidimensional Cubes, Tabular Models, DAX, MDX, semantic modeling, cube processing, and performance optimization.
Proficiency in database management, data warehousing, dimensional modeling, semantic modeling, SSAS Cubes, Tabular Models, and curated dataset development using platforms such as 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 multiple systems and platforms.
Experience working with APIs, cloud platforms (Azure, AWS, GCP), enterprise applications, and structured and semi-structured data sources including JSON, XML, and API payloads, with the ability to parse, transform, validate, and integrate data into data warehouses, semantic models, and reporting solutions.
Proficiency with Business Intelligence tools including Power BI, Microsoft Fabric, SSRS, semantic models, dashboards, data visualization, and self-service analytics best practices.
Experience with programming and scripting languages such as SQL, Python, PowerShell, JavaScript, or similar technologies to support data engineering, automation, integrations, and reporting solutions.
Understanding of software development lifecycle practices, source control, testing methodologies, CI/CD processes, and deployment management.
Experience leveraging AI-enabled technologies, Microsoft Copilot, Generative AI solutions, Large Language Models (LLMs), and semantic models to enhance reporting, analytics, automation, and self-service data experiences.

Responsibilities

Design, develop, and maintain SQL views, stored procedures, functions, and database objects.
Build and support data integrations between various platforms, APIs, and enterprise data sources.
Develop and maintain data warehouse structures, dimensional models, semantic models, curated business datasets, and analytical data assets including SSAS Multidimensional Cubes, SSAS Tabular Models, measures, hierarchies, aggregations, partitions, processing strategies, and performance optimization.
Design and support ETL/ELT pipelines for efficient movement and transformation of operational and reporting data.
Monitor and maintain 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 enterprise business intelligence solutions including Power BI datasets, semantic models, dashboards, scorecards, executive reporting, and self-service analytics capabilities.
Develop reusable KPI frameworks, reporting standards, business rules, calculations, and governed semantic models that support consistent enterprise reporting.
Administer Power BI workspaces, gateways, security models, deployment pipelines, source control, testing, release management, and reporting governance processes.
Develop monitoring, validation, reconciliation, and alerting solutions to ensure data quality, reporting accuracy, platform reliability, and enterprise performance standards.
Maintain reporting documentation, metadata, data dictionaries, and reporting lifecycle management processes.
Perform trend analysis across contact center operational, financial, workforce, and customer experience metrics.
Analyze volumes, service levels, abandonment rates, productivity, occupancy, callback utilization, queue performance, customer experience, and operational efficiency metrics.
Identify trends, anomalies, root causes, and opportunities for process improvement.
Develop forecasting models and support workforce planning activities.
Communicate findings and recommendations to operational leaders and executive stakeholders.
Design and monitor key performance indicators supporting business objectives.
Evaluate and implement AI-enabled analytics solutions to improve reporting automation, insight generation, anomaly detection, and decision support.
Design datasets and semantic models optimized for natural language querying and AI-powered analytics experiences.
Utilize Microsoft Copilot, Power BI AI capabilities, Microsoft Fabric, and approved enterprise AI platforms to enhance reporting and analytics workflows.
Identify opportunities to automate manual analytics processes through generative AI and workflow automation.
Develop AI-assisted reporting templates, prompt libraries, and reusable insight-generation frameworks.
Support implementation of conversational analytics and natural-language reporting capabilities.
Research emerging AI, machine learning, and analytics technologies and recommend practical business applications.
Partner with business stakeholders to gather requirements and define analytics solutions.
Translate business objectives into scalable reporting and data strategies.
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.