• Design and implement scalable data solutions within the Microsoft Fabric ecosystem • Strong experience building reports and dashboards in Power BI • Stand up and configure Fabric services to support data ingestion, transformation, modeling, and reporting • Develop and optimize semantic models that support both reporting and broader data consumption needs • Establish and guide best practices for workspace organization, capacity management, and workload distribution • Design and implement secure data access patterns, including integration between Snowflake and Fabric • Evaluate and support Snowflake-to-Fabric connectivity, mirroring strategies, and performance optimization • Identify opportunities to leverage Fabric capabilities such as data agents, automation tooling, and DevOps integration • Build and support automation solutions, including replacements for legacy processes (e.g., Oracle BI agents, scheduled workflows) • Partner with client teams to guide platform adoption and increase internal capability through collaborative sessions • Contribute to the development of standards, reusable patterns, and migration playbooks for long-term sustainability

Role Description As Data Engineer, AI, you will play a key role in building and advancing LVT’s data platform — contributing across the full data engineering lifecycle, from ingestion and transformation to semantic modeling and delivery — while also helping build the data infrastructure that powers LVT’s AI initiatives, including RAG pipelines and Snowflake Cortex models. This is a core engineering role with an AI edge: you’ll keep the data platform running with precision and reliability, and you’ll be the person who makes sure our AI systems have the clean, well-structured data they need to perform. LVT is a flexible-first company. This role can be performed remotely, with a preference for candidates who can work from our American Fork, UT office. Role Responsibilities - Design, build, and maintain scalable ELT pipelines that move data reliably from source systems into a clean, well-governed data platform. - Develop and maintain semantic models that expose consistent, trusted business definitions across reporting and analytics surfaces. - Own data quality — implement validation, monitoring, and alerting frameworks that catch problems before they reach stakeholders. - Optimize Snowflake performance across ingestion, transformation, and storage, including dynamic tables, clustering, and query tuning. - Architect and build the data infrastructure required for RAG applications, including vector storage, chunking strategies, and retrieval pipelines. - Collaborate with AI/ML engineers to support Snowflake Cortex model development with well-structured, context-rich training and inference data. - Partner with analytics engineers, data scientists, and business stakeholders to translate requirements into durable data solutions. - Document data architecture, pipeline design, and modeling decisions to support team knowledge and long-term maintainability. Qualifications - 5+ years building and maintaining production-grade pipelines using SQL, Python, and modern ELT tools such as dbt, Fivetran, or Airflow. - Deep hands-on experience with Snowflake, including performance optimization, dynamic tables, and familiarity with Cortex AI capabilities. - Ability to design and maintain semantic or metrics layers that enforce consistent business logic across the organization. - Working knowledge of RAG architectures and the data patterns — chunking, embedding, retrieval — that support LLM-driven applications. - Strong instinct for reliability — you instrument pipelines with observability and validation from the start. - Comfortable owning work from scoping through production — you define the problem, build the solution, and stand behind the outcome. - Able to work fluidly with engineers, analysts, and non-technical stakeholders, translating ambiguity into clear data solutions. Benefits - We believe you do your best work when your whole life is supported. - We invest in our crew’s health, families, and financial futures with a benefits package designed to support you inside and outside the office. Company Description LVT is redefining how businesses operate in the physical world, moving beyond traditional security solutions to deliver AI-driven, actionable intelligence that makes sites smarter, safer, and more secure. - Named one of the Financial Times’ Fastest Growing Companies 2025. - #10 on the Inc. 5000 Rocky Mountain Regional list for 2025. - Our CEO, Ryan Porter, was named an EY Entrepreneur of the Year 2025. - Our CTO, Steve Lindsey, was inducted into the Silicon Slopes CTO Hall of Fame in 2024. - We were named one of The Software Report’s Top 100 Software Companies of 2023. - Winner of the Security Today Govies Award for 2025.

• Support the Louisiana State Office of Technology in designing and managing a comprehensive data framework. • Establish the vision and blueprint for the organization's data ecosystem. • Lead efforts in data modeling and design, software development support, and database administration. • Write and maintain complex SQL queries to support reporting, analysis, and data operations. • Collaborate with stakeholders to identify data requirements and translate them into scalable architectural solutions.

Role Description At Dreamix, we’re actively seeking a skilled Data Engineer to join our growing team. We’re looking for someone with a strong foundation in data engineering who focuses on building clean, efficient, and scalable data solutions. If you enjoy working in a collaborative environment and want to contribute to meaningful data-driven projects, we’d be glad to hear from you. - Design, build, and maintain data pipelines across ingestion, transformation, and delivery layers - Implement transformations that apply business rules and produce clean, governed datasets - Ensure pipelines are performant, observable, and maintainable - Develop data quality checks, tests, and validations to meet data contracts and business requirements - Investigate and resolve data quality issues in development and production - Adhere to agreed engineering standards, naming conventions, and code review practices - Ensure all work is documented, version-controlled, and maintainable by the team - Collaborate with engineering and data stakeholders on pipeline design and data requirements Qualifications - Hands-on experience in data engineering (3-6 years) with Databricks exposure in a production environment - Strong Spark SQL skills with proven experience building data pipelines - Experience with at least one data transformation framework (e.g. DBT, DLT, Spark SQL, or similar) - Solid understanding of data modelling concepts (dimensional, relational, or entity-based) - Familiarity with version control (Git) and engineering best practices - Ability to operate effectively within a structured, standards-driven delivery environment Requirements - Exposure to data quality frameworks or testing tooling - Experience in regulated industries or enterprise-scale data environments - Familiarity with CI/CD for data pipelines Benefits - A warm and supportive work environment where you can reach your full potential - Flexible working hours that allow you to balance your work and personal life - Unlimited home office to help you stay productive and focused - Opportunities for professional development, including certifications and training - Additional benefits for academic teaching and speaking engagements - Knowledge-sharing sessions where you can learn from our Dreamix team - Team and company-wide events that bring us together - Amazing week long summer office and winter office initiatives - Additional health insurance and dental allowance to ensure your well-being - Multisport card to encourage a healthy and active lifestyle - Office massages to help you relax and unwind