Senior Data Engineer

About the Role

Karbon is transforming how modern businesses manage financial and operational data. As a Senior Data Engineer, you'll be a hands-on technical engineer designing and executing critical data platform initiatives — building the scalable, secure foundations that power AI-driven insights, real-time analytics, and next-generation data experiences serving thousands of customers and millions of transactions.

You'll work closely with our Lead Data Engineer and cross-functional teams across analytics, BI, AI, and product.

What You'll Own

• Design and implement distributed data pipelines and ETL/ELT infrastructure using Databricks, with medallion architecture (bronze/silver/gold) and clear data contracts and lineage.
• Build multi-tenant data infrastructure with robust isolation, performance, and cost management across cloud regions.
• Lead integration of our AI-powered analytics platform with Databricks, including semantic layers, row-level security, and self-serve governance patterns.
• Design and implement graph-based data structures for relationship mapping and client intelligence, integrating graph databases with Databricks as the source of truth.
• Own the security and governance model: RBAC, PII masking, data residency, compliance monitoring, and tenant isolation.
• Establish data engineering best practices: testing frameworks, CI/CD for data transformations, observability, and incident response.
• Mentor junior engineers, lead architecture discussions, and communicate technical decisions to both technical and non-technical stakeholders.

What Sets You Apart

Required

• 7+ years as a data engineer, with 2+ years in a senior or staff-level role.
• Deep expertise with cloud data warehouses, Databricks preferred.
• Proficiency with ELT/ETL tools (Fivetran or similar) and transformation frameworks such as dbt.
• Strong SQL and query optimisation skills at scale; deep understanding of dimensional modeling, fact tables, and conformed dimensions.
• Experience implementing row-level security and RBAC in data systems, and familiarity with privacy regulations (GDPR, CCPA, HIPAA).
• Infrastructure-as-Code experience (Terraform or equivalent).
• You've shipped data platforms under real operational pressure and understand the trade-offs between perfect architecture and shipping on time.

Highly Valued

• Graph databases (Neo4j, Amazon Neptune, ArangoDB) and graph query patterns.
• Real-time/streaming data (Kafka, Spark Streaming, Fivetran CDC).
• Python or Scala for data processing beyond SQL.
• ML infrastructure, feature stores, or MLOps tooling.
• Multi-tenant SaaS data architectures and isolation patterns.

Our Core Data Stack

• Platform: Databricks (core compute and transformation layer) 
• Ingestion: Fivetran and custom pipelines 
• Transformation: DLT/ dbt with medallion architecture 
• Cloud: Microsoft Azure 
• Graph: Neo4j / Ara