Role Description The Analytics Engineer is responsible for modeling data to provide clean, accurate datasets for use across the organization. They understand how data influences and empowers business processes, products, and services. They enable their partners such as data scientists, data analysts, engineers, and others by building and maintaining high-quality, reliable data marts. - Designs, builds, and deploys various sophisticated data models that support multiple use cases across different products or domains. - Solves data integration problems, utilizing optimal ETL patterns, frameworks, query techniques, sourcing from structured and unstructured data sources. - Optimizes pipelines, dashboards, frameworks, and systems to facilitate easier development of data products. - Builds foundational knowledge of Symetra products, workflow, and business context in order to anticipate future analytics opportunities. - Follows engineering best practices and develops cross-functional partnerships. Qualifications - 2–5 years of experience in analytics engineering, data engineering, business intelligence, or a related data-focused role. - Experience designing, building, and maintaining data models and data marts that support business reporting and analytics. - Strong knowledge of ETL processes, data integration, and transforming data from structured and unstructured sources. - Proficiency with SQL and at least one programming language (such as Python or similar) for data analysis and engineering. - Experience optimizing data pipelines, queries, and analytics solutions for performance and scalability. - Understanding of data modeling best practices, data quality, and engineering standards. - Strong analytical and problem-solving skills with the ability to translate business needs into reliable data solutions. - Effective communication and collaboration skills with the ability to partner across technical and business teams. - Bachelor's degree in Computer Science, Data Analytics, Information Systems, or a related field (or equivalent experience). - High school diploma required. Requirements - Employer work visa sponsorship and support are not provided for this role. - Applicants must be currently authorized to work in the United States at hire and must maintain authorization to work in the United States throughout their employment with our company. - Minimum Internet Speed: 100 Mbps download and 20 Mbps upload, in alignment with the FCC's definition of "broadband." - Internet Type: Fiber, Cable (e.g., Comcast, Spectrum), or DSL. - Not Permissible: Satellite (e.g., Starlink), cellular broadband (hotspot or otherwise), any other wireless technology, or wired dial-up. Benefits - Flexible full-time or hybrid telecommuting arrangements. - Plan for your future with our 401(k) plan and take advantage of immediate vesting and company matching up to 6%. - Paid time away including vacation and sick time, flex days and ten paid holidays. - Give back to your community and double your impact through our company matching.

• Serve as a domain authority for nVent Data Solutions products, including their application, for nVent functions • Provide first-line product support by providing help to customers and colleagues using nVent Data Solutions and Electrical Connections • Evaluate customer RFQs and build costing/quotes with technical and commercial content • Provide technical application assistance to identify modified and engineered products based on customer specifications and application requirements • Prepare and submit quotations & proposals of non-standard products using internal CPQ and ERP systems • Conduct product training for customers and train distributors on quoting tools • Prepare compliance documents against customer specifications • Lead strategic projects for product improvements, cost reduction, product consolidation, and new product development • Review training literature for technical accuracy including installation guides and procedures, operations manuals, and online learning • Represent nVent in industry codes and standards committees • Provide market-specific intelligence and feedback on products and services to the commercial teams • Assist commercial teams with voice-of-customer (VOC) visits • Plan activities together with the Sales Leader • Identify the project in the closing phase with the sales team and provide vital technical support • Advises their manager about all situations, developments, and occurrences that are significant for the manager or are requested by them

• Develop and implement scalable and performant solutions. • Partner, as a peer, with Engineering Managers, Product Managers, and stakeholders throughout Aledade to develop and execute technical roadmaps using Agile processes. • Mentor and coach more junior engineers including thorough pull request reviews for other developers and be receptive to critical feedback on your own work.

• Influence technical strategy: Define and drive the long-term technical roadmap for Affirm’s Lakehouse Platform across Apache Iceberg, Spark, Snowflake, and cloud-native storage, balancing scalability, reliability, governance, performance, and cost. • Design and develop: Architect and implement platform capabilities that make analytical data secure, trustworthy, discoverable, and easy to use across Affirm’s engineering, analytics, machine learning, and business teams. • Strengthen governance and access controls: Design and operate secure, auditable data access capabilities across Snowflake and the lakehouse platform, including RBAC, dynamic data masking, cataloging, lineage, classification, and privacy policy enforcement. • Improve analytics engineering foundations: Partner with Analytics Engineering to evolve data modeling, transformation pipelines, testing frameworks, documentation standards, and data quality practices that enable trustworthy self-service analytics. • Operate at scale: Establish best practices for lakehouse operations, including schema evolution, table maintenance, partitioning, compaction, observability, incident response, production support, and readiness for on-call operations. • Optimize performance and cost: Identify and execute improvements across analytical compute and storage, including Snowflake warehouse tuning, query optimization, storage layout, lifecycle management, cost attribution, and operational efficiency. • Collaborate cross-functionally: Partner with Infrastructure, Lakehouse Analytics, Analytics Engineering, Machine Learning, BI, Product Engineering, and SRE to translate stakeholder needs into durable platform architecture. • Innovate: Stay ahead of industry trends in lakehouse architecture, open table formats, analytical compute engines, data governance, privacy engineering, semantic layers, agentic data tools, and AI-ready data infrastructure. • Build teams: Mentor engineers, raise technical quality, and foster an inclusive culture of design rigor, operational excellence, and continuous learning.