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Designs and optimizes enterprise-scale semantic models in Microsoft Fabric and Power BI. Responsibilities include dimensional and star-schema modeling, fact and dimension tables, SCDs, advanced DAX measures, SQL optimization, relationships, hierarchies, KPIs, and Tabular Editor/TOM development. The role focuses on improving query performance, data connections, memory utilization, scalability, and maintainability while collaborating with BI, data, analytics, and business teams.

Designs scalable enterprise data and BI architectures, including data warehouses, dimensional models, databases, ETL/ELT pipelines, and integrations. Develops complex SQL solutions, supports Power BI or Tableau reporting, and applies Python or R for automation. Collaborates with technical and business stakeholders, establishes governance and security standards, optimizes performance and reliability, modernizes data platforms, and documents architectural decisions and data flows.

Develop and maintain enterprise Power BI reports, dashboards, and scalable semantic models. Build DAX measures, write SQL queries, optimize tabular models and report performance, analyze data quality, and support cloud or on-premises BI environments. Collaborate with technical and business stakeholders, use Git for version control, and maintain documentation covering models, reports, business logic, dependencies, and deployment processes.

Designs and operates automated CI/CD infrastructure in Microsoft Azure using Terraform, Azure DevOps, containers, and orchestration platforms. Responsibilities include infrastructure automation, systems administration across Windows and Linux, scripting, Git management, production troubleshooting, API testing, software development, security integration, SDLC improvement, and internal tooling. The role collaborates across development, infrastructure, networking, and QA teams and includes occasional on-call support.

Design, build, and maintain scalable production data pipelines and cloud-based solutions in Microsoft Azure. Develop Python, SQL, Spark, Spark SQL, and PySpark workflows for data ingestion, transformation, integration, analytics, reporting, and machine learning. Monitor, troubleshoot, validate, and optimize data pipelines and large-scale processing workloads while collaborating with technical teams and stakeholders. Document architectures and follow software engineering best practices for testing, version control, and deployment.

Lead AI/ML and automation strategy, mentor teams, design scalable architectures, oversee AI initiatives, integrate solutions with enterprise applications, and communicate strategy to stakeholders.

Analyze large and complex datasets using SQL, Python, Spark, Spark SQL, and PySpark in Microsoft Azure environments. Responsibilities include data transformation, validation, profiling, reconciliation, quality analysis, root-cause investigation, scalable data process improvement, documentation, and communicating findings to technical and business stakeholders.

Develop Python, SQL, and REST API integrations across the full software development lifecycle. Gather customer requirements, translate them into technical specifications, build and test solutions, conduct code reviews, troubleshoot integrations, document deliverables, and manage technical projects through deployment. The role requires strong customer communication, software quality practices, TDD, unit testing, performance awareness, and collaboration with engineering teams. Azure DevOps, Git, CI/CD, and external customer integration experience are preferred.

Supports implementation, configuration, testing, troubleshooting, deployment, migration, and administration of Genesys Cloud CX contact center solutions. Configures users, queues, routing, Architect flows, schedules, permissions, integrations, and reporting. Assists with customer meetings, UAT, documentation, post-launch support, and production stabilization while escalating complex issues to senior engineers.

Submit a general application to join SMASH's talent network. Applicants are considered for future roles across software engineering, QA, DevOps, data, customer experience, sales, and product/project management. Candidates should demonstrate strong communication, professionalism, customer focus, teamwork, continuous learning, and English proficiency. The recruiting team reviews applications and contacts matches for open opportunities.