Full Job Description

Role Overview As a Senior Software Engineer on the Semantic Data Team, you'll contribute to designing, building, and maintaining control plane for Semantic layer and AI Native data platforms. You'll work closely with domain experts, data scientists, and product stakeholders to translate business concepts into frameworks that support development. You'll implement logic for classifications, KPIs, scoring algorithms, and business rules, ensuring traceability and data lineage. What You Will Do You'll engineer the Operational Backbone, transforming platform reliability by building sophisticated observability frameworks and automated quality gates. You'll drive self-service autonomy by developing intuitive portals and 'golden templates,' empowering domain teams to autonomously build, manage, and consume trusted data products. You'll champion platform governance by automating critical compliance and security policies. Why It Might Be a Fit You'll leverage AI coding assistants to accelerate development, critically reviewing AI output for correctness and alignment with business rules. You'll share patterns, prompts, and workflows that help the team get more leverage out of AI tooling, contributing to AI-native engineering practices across the Semantic Data Team. Requirements 4–8 years of experience in data engineering or software engineering with a focus on data transformation, modeling, or analytics platforms. Strong proficiency in SQL and at least one general-purpose language such as Python or Scala. Demonstrated experience as an AI-native engineer—using tools like Claude, GitHub Copilot, Cursor, or similar as a regular part of your development workflow. AI-Native Architecture: You are passionate about the future of data intelligence and have hands-on experience with LLM-driven architectures. Familiarity with modern AI engineering practices such as prompt design, Spec-Driven Development (SDD), and AI-assisted code review. Advanced Data Orchestration & Pipeline Reliability: You possess deep expertise in building and managing complex orchestration systems (specifically Airflow) and are obsessed with reliability. Infrastructure as Code (IaC) & Platform Engineering: You are fluent in the modern DevOps stack—including Terraform, Kubernetes, and CI/CD automation—allowing you to build self-healing, scalable infrastructure that minimizes operational toil. Enterprise Governance & Metadata Management: You have a proven track record of implementing automated governance, specifically utilizing DataHub or similar platforms to manage end-to-end lineage, cataloging, and RBAC policies that make security inherent to the data object. Observability & Incident Management: You understand that 'the platform is the product.' You bring experience building comprehensive observability frameworks (e.g., Grafana, xMatters integration) that move teams from reactive firefighting to proactive, automated alerting. Self-Service Mindset: You advocate for 'developer autonomy' over manual intervention. You have experience building intuitive portals and developer tools that enable domain teams to build, manage, and consume trusted data products independently. Solid understanding of data quality practices—including validation, enrichment, schema enforcement, and business rule encoding.

Skills and Technologies