Job Opportunities API

About Karbon Karbon is the global leader in AI-powered practice management software for accounting firms. We provide an award-winning cloud platform that helps tens of thousands of accounting professionals work more efficiently and collaboratively every day. With customers in 40 countries, we have grown into a globally distributed team across the US, Australia, New Zealand, Canada, the United Kingdom, and the Philippines. We are well-funded, ranked #1 on G2, growing rapidly, and have a people-first culture that is recognized with Great Place To Work® certification and on Fortune magazine's Best Small Workplaces™ List. About the Role Karbon is transforming how modern businesses manage financial and operational data. As Lead Data Engineer, you are the technical owner of our data platform — the person who sets direction, drives architecture, and is ultimately accountable for what the team builds and ships. You'll define how we design, build, and evolve a platform that powers AI-driven insights, real-time analytics, and next-generation data experiences for thousands of customers and millions of transactions. You'll be the primary technical voice in cross-functional conversations with analytics, BI, AI, and product teams — and the person who makes sure your team has the clarity, quality bar, and unblocking they need to deliver. What You'll Own Platform strategy and architecture — own the end-to-end design of our data platform: medallion architecture, data contracts, lineage, multi-tenancy, and the technical roadmap that keeps us ahead of scale. Cross-functional technical leadership — be the primary data engineering partner for analytics, BI, AI/ML, and product teams; lead design reviews, drive alignment on data contracts, and represent the platform in broader engineering conversations. Solution design — run architecture and design for all significant platform initiatives: pipeline infrastructure, semantic layers, graph database integration, streaming, and AI/ML feature engineering. Security and governance ownership — accountable for the platform's security model end-to-end: RBAC, row-level security, PII handling, data residency, tenant isolation, and compliance with privacy regulations. Engineering quality and standards — set and enforce the bar for how the team builds: testing frameworks, CI/CD for data transformations, observability, code review, and documentation. Team enablement — mentor and unblock senior and junior engineers; identify gaps in capability or process before they become delivery risks; ensure the team can consistently produce high-quality work. Operational excellence — own platform reliability: monitoring, alerting, incident response playbooks, and cost optimisation as data volume scales. What Sets You Apart Required 10+ years as a data engineer, with demonstrated experience in a lead, staff, or principal-level role. Deep expertise with cloud data platforms, Databricks strongly preferred. Proven track record designing and owning large-scale, multi-tenant data architectures — not just contributing to them. Strong command of ELT/ETL tooling (Fivetran, Airbyte, or similar), transformation frameworks (dbt), and dimensional modeling at scale. Experience driving technical direction across teams: leading design reviews, influencing architectural decisions, and communicating trade-offs clearly to technical and non-technical stakeholders. Experience implementing enterprise-grade security and governance: RBAC, RLS, PII masking, data residency, and privacy regulation compliance (GDPR, CCPA, HIPAA). Infrastructure-as-Code (Terraform or equivalent) and CI/CD ownership for data systems. You've mentored engineers, raised team capability, and unblocked delivery — not just individually shipped. Highly Valued Graph databases (Neo4j, Amazon Neptune, ArangoDB) and graph query patterns. Real-time/streaming data (Kafka, Spark Stream