SingleStore delivers a real-time, distributed SQL database that unifies transactional and analytical workloads.
Engineers build cloud-native software for demanding data-intensive applications, owning their work end to end.
About the Flow team
SingleStore Flow is an enterprise data migration and integration product that helps customers move data into SingleStore reliably and at scale.
The team builds systems supporting schema transfer, bulk data loading, real-time Change Data Capture (CDC), large-table migrations, and a native experience in SingleStore Helios.
Flow spans Java-based engines, source and destination connectors, database internals, performance and memory management, Helios services and APIs, observability, test automation, Flow AI Agent and signed production release delivery.
The product works across heterogeneous database environments, including MySQL, PostgreSQL, Oracle, SQL Server, MongoDB, SAP HANA, Snowflake, Salesforce, and SingleStore-as-a-source.
Responsibilities
Set technical direction for significant areas of Flow, including the migration engines, CDC pipeline, schema evolution, large-table migration, source-to-target data correctness, Flow APIs, Helios integration, and agent-assisted migration workflows.
Lead the design and delivery of large, complex, release-defining projects from problem definition through production rollout.
Make pragmatic architecture and build-versus-defer decisions that balance customer value, reliability, performance, maintainability, and delivery speed.
Design and implement production-quality software while remaining hands-on in the codebase.
Solve difficult, ambiguous problems involving data consistency, replication, schema drift, throughput, memory use, concurrency, failure recovery, and backward compatibility.
Establish a high bar for technical design, code quality, testing, observability, security, and operational readiness.
Drive root-cause analysis for customer-impacting issues and ensure that incidents result in durable fixes, better tests, improved diagnostics, or clearer operational safeguards.
Improve the team's ability to operate Flow in production through runbooks, dashboards, release discipline, incident response, and shared ownership of service health.
Partner closely with Product Management, Engineering, Support, Solutions, and customers to translate real-world migration requirements into robust technical solutions.
Mentor engineers, lead design and code reviews, distribute technical context, and help develop the next generation of technical leaders.
Create clear technical documentation that makes architecture, APIs, customer journeys, trade-offs, and operational procedures understandable to the broader engineering organization.
Advance AI-native development practices and agentic capabilities that improve engineering productivity and make customer migrations more self-serve.
Requirements
Significant professional experience building and operating production software, typically 10+ years, or equivalent depth of experience and impact.
Expert-level experience with Java including the ability to debug and improve complex, long-lived enterprise-grade codebases.
Experience using JDBC with one or more databases, including working with SQL metadata, SQL datatypes, schema information, database-specific behavior, connection pooling, SQL execution, Apache Avro, Protocol Buffers, or similar serialization and integration technologies.
Strong understanding of databases and data-intensive systems, including transactions, replication, indexing, connection management, and data consistency.
Deep experience with MySQL and PostgreSQL.
Experience with Java performance engineering, including concurrency, thread pools, garbage collection, memory pressure, or back-pressure.
Hands-on experience with Change Data Capture or comparable streaming and replication technologies, such as database logs, logical replication, change tracking, checkpoints, or offsets.
Demonstrated experience designing reliable, scalable distributed systems where correctness, performance, and availability matter.
Experience with cloud-native services and container orchestration, preferably Kubernetes.
Track record of leading large technical initiatives and making architecture decisions across team or functional-area boundaries.
Strong testing discipline, including unit, integration, end-to-end, regression, performance, and failure-mode testing.
Experience investigating production issues, writing root-cause analyses, and converting operational learnings into engineering improvements.
Experience with observability, profiling, metrics, distributed tracing, and production dashboards.