AI-Driven BI Engineer

Vericast

San Antonio (TX)

On-site

USD 90,000 - 109,000

Full time

2 days ago

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Benefits offered by this job

Medical, dental and vision coverage

Generous PTO

Life insurance

Employee assistance program

Pet insurance

Job summary

Vericast, a financial services analytics partner, seeks a Senior BI Engineer to own analytics lifecycle from data acquisition to forecasting. You will design and maintain SQL views, ETL pipelines, and BI solutions using Power BI, SSAS, and AI enhancements.

Collaboration across IT and operations will drive semantic modeling, governance, and enterprise reporting standards. The role emphasizes AI-enabled analytics, natural-language querying, and modernization of reporting using Copilot, Fabric, and

Qualifications

Bachelor’s degree in Computer Science, Software Engineering, Information Systems, Data Science or related field required.
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.

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 BI 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.