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Chainalysis is the blockchain data platform trusted by organizations worldwide to investigate illicit activity, manage risk, and build innovative solutions on blockchain intelligence. The engineering team solves hard technical challenges to create products that build trust in cryptocurrencies, with global teams spanning Denmark, UK, Canada, and the USA.
In this Senior Software Engineer role focused on Aggregation & Search, you will own and improve the data ingest Java service for enriched transfers generation and aggregations. You'll design and tune PostgreSQL transaction batching, indexing, and replication strategies to handle write-heavy, high-throughput workloads. You'll contribute to the next-generation architecture by running proofs-of-concept, benchmarking latency, and writing architecture decision records (ADRs) to deliver cutting-edge solutions to production.
Key responsibilities include building and maintaining scalable API services on AWS that handle thousands of requests per second, automating network onboarding end-to-end, and debugging production issues across microservices while defining SLOs and participating in on-call rotation. You'll integrate LLM-based tools into daily engineering work and build agentic automation for operational tasks including automated incident triage, self-healing pipelines, and intelligent alerting.
Chainalysis emphasizes AI fluency as a core competency—not as a feature but as a new way of working. The company expects all employees to take ownership of AI-driven output, develop these capabilities independently, and collaborate across teams to reinvent how work gets done.
REQUIREMENTS:
- 8+ years with PostgreSQL in production: schema design, query optimization, partitioning, replication, and performance tuning under write-heavy, high-throughput workloads
- 8+ years building Java Spring Boot services: REST APIs, JDBC, connection pooling, and JVM performance profiling
- Experience with Kafka or equivalent streaming systems: consumer groups, offset management, and partition lag debugging
- Track record operating distributed systems on AWS: microservices, multi-silo deployments, Terraform
- Strong cross-system debugging skills: tracing serving delays from Datadog metrics to Humio logs to code paths
- Comfort with AI-assisted development and agentic engineering practices
- Bias to ship and iterate alongside product and design partners
- Genuine excitement for significantly scaling large data systems
Core technologies required: PostgreSQL, Java Spring, Kafka. Expected familiarity: AWS, Kubernetes, Terraform, Python, Github/Github Actions, DataDog, Humio, PagerDuty.
Nice-to-have: database migration experience, Flink/Spark/lakehouse formats (Delta Lake, Iceberg, Parquet), Kubernetes operations (StatefulSets, HelmReleases), mentoring engineers and driving technical decisions through RFCs/ADRs, interest in cryptocurrency.
