Customer Support Developer (Databases)

Airbyte

23h•Remote

About The Position

Airbyte is the open-source standard for data movement, enabling data teams to move data from various sources to data warehouses, lakes, and AI applications. With a strong adoption and significant funding, Airbyte is now building frontier agentic data infrastructure for AI agents. The company's mission is to make data available and actionable everywhere. They operate with a product-led growth philosophy, aiming to build an awesome product that users love, while maintaining a scrappy, experimental approach in the AI-native landscape.

Requirements

2+ years in software engineering, data engineering, technical support, DevOps, QA, or a 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. You must be able to read, write, and debug JVM-based connector code. You'll be contributing to database sources and destinations, the Bulk CDK, and automation tooling.
Hands-on experience with relational databases, data warehouses, or data lakes, including concepts like CDC (Change Data Capture), schema evolution, and query optimization.
Experience with JDBC and common database drivers, and comfort debugging connection, authentication, SSL, and SSH tunnel issues.
Understanding of cloud platforms (AWS, GCP, or Azure) and data integration concepts, including ELT/ETL workflows.
Strong troubleshooting instincts, clear communication with both technical and non-technical stakeholders, and a growth mindset that keeps you improving even when things get hard.
High tolerance for ambiguity and a natural self-starter.
Flexibility to work Sun–Thu, Mon–Fri, or Tue–Sat shifts.

Nice To Haves

Experience with PostgreSQL, MySQL, MSSQL, Oracle, MongoDB, Snowflake, BigQuery, Redshift, ClickHouse, or similar relational and non-relational systems.
Experience with data lakes and open table formats (Iceberg, Delta Lake), and cloud object storage (S3, GCS, Azure Blob).
Familiarity with Airbyte's Bulk CDK or contributions to open-source database connectors.
Experience with container orchestration tools like Kubernetes or Docker and multi-tenant architectures.
Background supporting developer-facing or embedded/platform products in a B2B SaaS context.
Experience with CI/CD pipelines and GitHub-based open-source workflows.
Experience with AI-assisted development tools and building automated playbooks or Runbooks.

Responsibilities

Serve as the primary technical escalation point for database-related customer issues, responding via email, ticketing systems, and video calls with precision and clarity.
Triage and prioritize incoming issues with urgency, consistently meeting SLA targets while leveraging AI tools to work smarter and resolve issues faster.
Dig into complex issues across relational databases, data warehouses, data lakes, and cloud object storage, not just finding workarounds but partnering with Engineering to root-cause and drive real fixes.
Reproduce customer-reported bugs by inspecting connector logs, query plans, replication slots, transaction logs, sync state, and destination table state, and document findings with enough technical detail for Engineering to act on immediately.
Support customers through onboarding and troubleshooting for SSH tunnels, network configuration, database user permissions, CDC setup (WAL/binlog/redo logs), and warehouse/lake authentication.
Get hands-on with customers building and debugging integrations, helping them navigate Airbyte's database sources and destinations with confidence, from authentication and SSL/SSH setup to CDC, schema evolution, incremental cursors, and typed destination tables.
Validate database version compatibility across supported engines and releases, maintain testing environments, and reproduce customer-reported behavior on real database and warehouse instances.
Support customers writing to data warehouses (Snowflake, BigQuery, Redshift), data lakes and object storage (S3, GCS, Azure Blob, Databricks, Iceberg), and databases (Postgres, MySQL, MSSQL, ClickHouse), including schema evolution and typed-columns behavior.
Help customers running database sources (PostgreSQL, MySQL, MSSQL, Oracle, MongoDB, and more) troubleshoot replication behavior, cursor selection, full-refresh vs. incremental vs. CDC trade-offs, and sync state recovery.
Contribute directly to Airbyte's open-source database connectors and the Java/Kotlin Bulk CDK: fix bugs, improve error handling, harden schema-evolution and CDC paths, and submit pull requests to the Airbyte repository.
Review and test community contributions to database sources and destinations, helping external contributors land high-quality changes.
Stay sharp on Airbyte's connector catalog, new database and destination releases, and platform updates so your guidance is always accurate and timely.
Be the voice of the customer within Airbyte, working closely with Engineering and Product to surface issues, advocate for feature requests, and ensure customer pain points actually influence the database reliability and performance roadmap.
Partner with Solutions Engineering and Sales Engineering to provide white-glove technical onboarding for enterprise customers, including CDC architecture reviews, destination schema modeling, and production readiness assessments.
Train and mentor Technical Support Engineers on database connector concepts, including JDBC fundamentals, CDC patterns, schema evolution, query optimization, destination typing and normalization, and the Airbyte protocol (spec, discover, check, read, write).
Partner with Sales and Customer Success for technical conversations, onboarding, and expansion efforts, bringing the kind of product depth that helps close and retain customers.
Create and maintain internal and external knowledge base articles, troubleshooting guides, and database connector documentation to support scalability.
Document research and troubleshooting processes (including CDC debugging, destination schema reconciliation, and performance tuning runbooks) to aid faster ticket resolution and team knowledge sharing.
Identify AI-driven opportunities for automation and process improvements that reduce support load and improve the customer experience.
Embrace AI-assisted workflows and contribute to developing playbooks and skills that encode repeatable troubleshooting procedures, connector debugging patterns, and onboarding Runbooks, enabling the team to scale expertise through automation.
Spearhead initiatives to fill organizational or support gaps and take ownership of unique projects.