Senior Database Administrator at Kraken

Building the Future of Open Finance Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system. Before you apply, we encourage you to explore our culture page to understand what drives us and how we work. The Team You will join a senior team of DBAs, SREs, and platform engineers responsible for the database and vector data platforms behind Kraken's most critical services. The group combines deep operational expertise with a platform mindset: we design systems that let engineering teams move quickly while preserving strong guarantees around performance, correctness, security, and reliability. The team is entering an important phase of evolution as Kraken continues to expand globally and as AI-enabled product and internal platform use cases grow. Over the next year, we are focused on strengthening PostgreSQL operational excellence, building reliable vector data capabilities, preparing for significant future scale, and increasing automation and self-service so database operations become safer and more efficient at scale. This is not a traditional keep-the-lights-on DBA team. Our work centers on scaling high-throughput PostgreSQL environments, operating vector search and embedding stores with production discipline, shaping reliable patterns for high-traffic systems, and transforming operational knowledge into automated, auditable workflows that uplift the engineering organization. The Opportunity Scale and tune high-throughput PostgreSQL clusters that support continued global expansion and new product initiatives. Own PostgreSQL reliability fundamentals: WAL behavior, checkpoints, autovacuum, query planning, locking, replication lag, backup/restore, and capacity planning. Help build and operate vector data capabilities, including pgvector and dedicated VectorDB platforms where appropriate. Define production patterns for embeddings, approximate nearest neighbor indexes, metadata filtering, recall/latency tradeoffs, reindexing, data freshness, and drift management. Strengthen high-availability, disaster-recovery, PITR, and backup approaches through sound design and regularly validated procedures. Reduce manual operational work by building automation, improving process consistency, and enabling safe, low-friction database workflows. Improve observability and alert quality by championing meaningful metrics, reducing noise, and ensuring operational clarity across PostgreSQL and vector workloads. Enhance database security through robust access controls, disciplined patching and upgrade practices, encryption, auditability, and secure operational patterns. Contribute to modern platform initiatives, including containerized environments, infrastructure-as-code workflows, GitOps, reproducible deployments, and self-service dat