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Vericast

Marketing technology and services provider

Business Intelligence Engineer

Business IntelligenceConfirmed live in the last 24 hours
Full-timeSan Antonio, TX, USA$90k - $109k /yrHybrid

About the Job

Requirements

  • 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 instead.
  • 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 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 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 business intelligence 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 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 that support AI-enabled reporting and natural language analytics.
  • Experience using Python, JavaScript, PowerShell, or similar scripting or 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 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 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 such as Azure, AWS, and GCP, enterprise applications, and structured and semi-structured sources including JSON, XML, and API payloads; 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, and JavaScript 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, 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 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.
  • Use 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.
  • Communicate with Contact Center Operations, Business Intelligence, IT, Application Development, and external vendors to gather requirements, resolve data and reporting issues, and deliver actionable insights.
  • Present analytical findings, recommendations, and reporting outcomes to operational leaders and executive stakeholders, translating complex technical information into clear, business-focused guidance.
  • Exercise independent judgment in designing data models, reporting solutions, integrations, and analytics processes that support operational and strategic business decisions.
  • Evaluate data quality, reporting risks, automation opportunities, and emerging technologies, and make recommendations that influence analytics standards, platform improvements, and leadership decision support.

About the Company

Vericast

Marketing technology and services provider

Vericast helps brands engage customers and grow revenue by pairing marketing technology with professional services. It designs and runs campaigns that improve the customer experience and maximize the impact of media investments, with revenue coming from digital products, coupon redemptions, and printed check orders. The company serves many industries—from retail to healthcare to telecom—using award-winning technology and deep marketing expertise. Its goal is to help clients navigate changing markets and achieve profitable growth through effective customer engagement.

Company size
501-1,000
Company stage
Not listed
Total funding
Not listed
Headquarters
San Antonio, TX
Founded
Not listed

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