Lead Data Engineer

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.

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.

• 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.

• 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.

• Graph databases (Neo4j, Amazon Neptune, ArangoDB) and graph query patterns.
• Real-time/streaming data (Kafka, Spark Streaming, Fivetran CDC).
• ML infrastructure, feature stores, or MLOps tooling.
• Experience shaping data platform strategy in a scaling SaaS environment.

• Platform: Databricks (core compute and transformation layer) 
• Ingestion: Fivetran and custom pipelines 
• Transformation: DLT/ dbt with medallion architecture 
• Cloud: Microsoft Azure 
• Graph: Neo4j / ArangoDB (evolving) 
• Observability: Datadog
• IaC: Terraform

Our architecture continues to evolve toward real-time streaming, graph intelligence, and AI-native data experiences. If you care about platform ownership, engineering excellence, and building a team that ships with confidence — you'll feel right at home here.

Karbon embraces diversity and inclusion, aligning with our values as a business. Research has shown that women and underrepresented groups are less likely to apply to jobs unless they meet every single criteria. If you've made it this far in the job description but your past experience doesn't perfectly align, we do encourage you to still apply. You could still be the right person for the role!

We recruit and reward people based on capability and performance. We don’t discriminate based on race, gender, sexual orientation, gender identity or expression, lifestyle, age, educational background, national origin, religion, physical or cognitive ability, and other diversity dimensions that may hinder inclusion in the organization.

Generally, if you are a good person, we want to talk to you. 😛

If there are any adjustments or accommodations that we can make to assist you during the recruitment process, and your journey at Karbon, contact us at people.support@karbonhq.com for a confidential discussion.

At this time, we request that agency referrals are not submitted for this position. We appreciate your understanding and encourage direct applications from interested candidates. Thank you!