Design, build, and operate scalable data pipelines and services that ingest and unify customer support signals across channels—voice, chat, Copilot, and knowledge base—powering an AI-native support insights and analytics platform. Develop governed semantic models and Power BI datasets that shift analytics from report-heavy delivery to semantic-model-led, self-serve, AI-native insights. Build AI-native capabilities—data agents, Copilot experiences, knowledge agents, and self-serve report builders—including retrieval, orchestration, and evaluation of model quality. Ensure data quality, lineage, and governance across the golden layer so insights are trustworthy, cited, and policy-compliant. Write clean, secure, well-tested code (SQL, Python, C#); participate in code reviews; and uphold engineering excellence and coding standards. Monitor and improve the reliability, performance, and cost efficiency of pipelines and services, participating in live-site, on-call, and incident resolution as needed. Partner with product managers, applied scientists, analysts, and stakeholders to turn support KPIs (e.g., CSAT) and reporting needs into well-scoped solutions delivered incrementally within an agile team. Bachelor's degree in Computer Science, Engineering, or a related field AND 2+ years of professional software or data engineering experience; OR equivalent practical experience. Proficiency in SQL and at least one modern programming language such as Python, C#, or Scala. Demonstrated experience designing, building, testing, debugging, and shipping production data or software solutions. Experience building semantic models and Power BI (DAX) for self-serve, AI-native analytics. Experience building AI/LLM-powered capabilities—data agents, copilots, retrieval-augmented generation, or model evaluation—and familiarity with the Model Context Protocol (MCP). Familiarity with data quality, lineage, and governance practices over large, multi-source datasets. Familiarity with CI/CD, observability, and live-site/DevOps practices. Experience with customer service and support data, or with large-scale, customer-facing data platforms. Strong collaboration and communication skills and a growth mindset, with genuine passion for applying AI to transform how work gets done.
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