Role Description We are looking for a Senior Data Engineer to join a high-impact project focused on accelerating a Microsoft Fabric migration initiative. This is a hands-on role where you will play a key part in designing, building, and migrating data solutions into a modern data platform leveraging Microsoft Fabric and the Azure ecosystem. You will work closely with the Data leadership team to help execute a near-to-long-term data roadmap. - Lead and support the migration of existing data platforms into Microsoft Fabric - Design and implement scalable data pipelines and workflows - Build and optimize data models within a Lakehouse architecture - Work with large datasets, ensuring performance, reliability, and data quality - Collaborate with stakeholders to translate business requirements into technical solutions - Contribute to the evolution of the organization’s modern data platform - Ensure best practices in data engineering, governance, and security Qualifications - 5+ years of experience in Data Engineering - Strong experience with Azure Data Services (Data Factory, Synapse Analytics, Data Lake, etc.) - Hands-on experience with Microsoft Fabric (highly preferred) or strong willingness to ramp up quickly - Advanced SQL skills and solid experience with Python - Experience building and managing ETL/ELT pipelines - Strong understanding of modern data architectures (Lakehouse, Medallion, etc.) - Experience working in cloud-based environments (Azure required) - Proven experience in data platform migrations or large-scale data transformations Requirements - Experience with Power BI and semantic models (nice-to-have) - Familiarity with Delta Lake (nice-to-have) - Experience in Agile environments (nice-to-have) - Exposure to data governance and data quality frameworks (nice-to-have) Benefits - 100% remote from anywhere - Competitive compensation in USD - Training allowances for upskilling - Work with global teams and top-tier clients - Home-office hardware setup - PTO for recharge and balance - People-first culture built on trust, autonomy, and impact Compliance & Equal Opportunity Launchpad is an equal opportunity employer committed to creating an inclusive environment for all applicants. We do not discriminate on the basis of race, color, religion, gender identity, sexual orientation, age, disability, or any other protected status under applicable laws in Canada and British Columbia. All candidate information will be handled confidentially and used solely for recruitment purposes in accordance with applicable privacy regulations.

• Help shape the future of digital (parcel) logistics by developing advanced analytics systems for own and 3rd-party systems. • Develop analytics applications based on the data provided by systems in a parcel sorting centre. • Collaborate with Product Management and R&D. • Work within interdisciplinary development teams, including machine control and system architecture.

• 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.