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Airbyte is the data and action layer for AI agents, providing fast, accurate, authenticated access to business data across hundreds of sources. The company has raised $181M from leading investors and operates as both an open-source standard for data movement and a production-grade platform for AI agents.
As a Customer Support Developer (Databases), you will combine hands-on development with technical customer support. This is not a traditional support role—you'll write Java and Kotlin, contribute to open-source database connectors, debug complex replication issues, and directly influence how customers move mission-critical data between databases, warehouses, and lakes.
Key responsibilities include:
**Customer Support & Technical Troubleshooting**
- Serve as the primary technical escalation point for database-related customer issues via email, ticketing, and video calls
- Triage and prioritize issues while meeting SLA targets, using AI tools to work more efficiently
- Investigate complex issues across relational databases, data warehouses, data lakes, and cloud object storage
- Reproduce bugs by inspecting connector logs, query plans, replication slots, transaction logs, and sync state
- Support customers with SSH tunnels, network configuration, database permissions, CDC setup, and warehouse/lake authentication
**Database Connector Development**
- Debug integrations and help customers navigate Airbyte's database sources and destinations
- Validate database version compatibility and maintain testing environments
- Support customers using Snowflake, BigQuery, Redshift, S3, GCS, Azure Blob, Databricks, Iceberg, PostgreSQL, MySQL, MSSQL, Oracle, MongoDB, and ClickHouse
- Troubleshoot replication behavior, cursor selection, and sync state recovery
- Contribute directly to open-source database connectors and the Java/Kotlin Bulk CDK
- Review and test community contributions to database sources and destinations
- Stay current on Airbyte's connector catalog and platform updates
**Cross-Functional Collaboration**
- Advocate for customer needs with Engineering and Product teams
- Partner with Solutions Engineering and Sales Engineering on enterprise onboarding and production readiness assessments
- Train and mentor Technical Support Engineers on database connector concepts, JDBC, CDC patterns, schema evolution, and the Airbyte protocol
- Support Sales and Customer Success with technical conversations and expansion efforts
**Knowledge & Process Improvement**
- Create and maintain internal and external knowledge base articles and troubleshooting guides
- Document research and debugging processes to enable faster ticket resolution
- Identify AI-driven automation opportunities to reduce support load
- Develop playbooks and skills that encode repeatable troubleshooting procedures
- Spearhead initiatives to fill organizational gaps
**Requirements:**
- 2+ years in software engineering, data engineering, technical support, DevOps, QA, or similar role supporting developers or technical users
- Fluency in SQL with hands-on experience investigating query plans, isolation levels, and performance bottlenecks
- Proficiency in Java or Kotlin; ability to read, write, and debug JVM-based connector code
- Hands-on experience with relational databases, data warehouses, or data lakes, including CDC, schema evolution, and query optimization
- Experience with JDBC and common database drivers; comfort debugging connection, authentication, SSL, and SSH tunnel issues
- Understanding of cloud platforms (AWS, GCP, or Azure) and data integration concepts (ELT/ETL)
- Strong troubleshooting instincts, clear communication with technical and non-technical stakeholders, and a growth mindset
- High tolerance for ambiguity and self-starter mentality
**Nice to have:**
- Experience with PostgreSQL, MySQL, MSSQL, Oracle, MongoDB, Snowflake, BigQuery, Redshift, ClickHouse, or similar systems
- Experience with data lakes and open table formats (Iceberg, Delta Lake) and cloud object storage
- Familiarity with Airbyte's Bulk CDK or open-source database connector contributions
- Experience with Kubernetes, Docker, or multi-tenant architectures
- Background supporting developer-facing or embedded/platform products in B2B SaaS
- Experience with CI/CD pipelines and GitHub-based open-source workflows
- Experience with AI-assisted development tools and building automated playbooks
