Business Intelligence Engineer

Vericast•San Antonio, TX

4h•$90,000 - $109,000

About The Position

Vericast is seeking a Business Intelligence Engineer to design, develop, administer, and continuously improve enterprise contact center analytics, business intelligence, and AI-enabled reporting solutions. The role owns the full 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 that support operational performance, customer experience, workforce optimization, financial reporting, and strategic decision-making. The position is a technical and analytical leader responsible for modernizing reporting through automation, self-service analytics, semantic modeling, and AI technologies such as Microsoft Copilot, Power BI AI capabilities, large language models, and enterprise AI solutions. It develops and maintains data integrations, SQL objects, warehouse and semantic models, ETL/ELT pipelines, Power BI solutions, reporting governance, data quality controls, forecasting, and AI-assisted analytics. The role also gathers business requirements, presents findings to operational and executive stakeholders, supports project implementation, and maintains analytics documentation and standards.

Requirements

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, database performance tuning, and analytical data structures.
Experience with 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.
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 BI platforms.
Experience gathering business requirements and translating them into scalable data, reporting, analytics, and self-service BI solutions.
Experience with 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, including views, stored procedures, functions, query optimization, 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 across multiple systems and platforms.
Experience with APIs, cloud platforms such as Azure, AWS, or GCP, enterprise applications, and structured or semi-structured data including JSON, XML, and API payloads; ability to parse, transform, validate, and integrate data into warehouses, semantic models, and reporting solutions.
Proficiency with BI tools including Power BI, Microsoft Fabric, SSRS, semantic models, dashboards, data visualization, and self-service analytics practices.
Experience with software development lifecycle practices, source control, testing methodologies, CI/CD processes, and deployment management.
Experience leveraging AI technologies, Microsoft Copilot, generative AI, large language models, and semantic models to enhance reporting, analytics, automation, and self-service data experiences.
Ability to communicate and collaborate with Contact Center Operations, BI, IT, Application Development, external vendors, operational leaders, and executive stakeholders, and to translate complex technical information into business-focused guidance.
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.
A bachelor's degree in Computer Science, Software Engineering, Information Systems, Data Science, or a related field is required; equivalent professional experience may be considered in lieu of a formal degree.

Responsibilities

Design, develop, and maintain SQL views, stored procedures, functions, and database objects.
Build and support data integrations across platforms, APIs, and enterprise data sources.
Develop and maintain data warehouse structures, dimensional and semantic models, curated business datasets, SSAS cubes and tabular models, measures, hierarchies, aggregations, partitions, processing strategies, and performance optimizations.
Design and support ETL/ELT pipelines for moving and transforming 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 BI solutions, including 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 for data quality, reporting accuracy, platform reliability, and performance.
Maintain reporting documentation, metadata, data dictionaries, and reporting lifecycle processes.
Analyze contact center operational, financial, workforce, and customer experience trends, including volumes, service levels, abandonment, productivity, occupancy, callback utilization, queue performance, and efficiency.
Identify trends, anomalies, root causes, and process improvement opportunities.
Develop forecasting models and support workforce planning.
Communicate findings and recommendations to operational leaders and executive stakeholders.
Design and monitor KPIs that support 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 to improve reporting and analytics workflows.
Identify opportunities to automate analytics processes with generative AI and workflow automation.
Develop AI-assisted reporting templates, prompt libraries, and reusable insight-generation frameworks.
Support conversational analytics and natural-language reporting capabilities.
Research emerging AI, machine learning, and analytics technologies and recommend practical business applications.
Gather stakeholder requirements and 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 audits and compliance activities related to reporting and data management.