Senior Platform Engineer, Data Persistence

Are you a platform engineer who thrives on designing scalable, resilient data systems that support real-world, enterprise workloads? Do you enjoy owning complex persistence challenges—balancing performance, reliability, and cost—while enabling product teams to move faster with confidence? Are you excited to shape the foundation of a cloud-native SaaS platform by building durable, high-availability data architectures that stand up to growth and change? If so, we invite you to be a part of our innovative team. As a Senior Platform Engineer on the Data Persistence team, you will play a critical role in designing, building, and optimizing the data systems that power Ridgeline’s enterprise SaaS platform. You’ll lead the evolution of our cloud-native, distributed data architecture—solving challenges around scale, performance, availability, and cost—while delivering a best-in-class developer experience. In this role, you will collaborate closely with application and infrastructure teams to develop efficient, resilient, and high-performance data solutions that directly support customer-facing workloads. You’ll leverage cutting-edge technologies—including AI tools like GitHub Copilot and ChatGPT—to enhance productivity, accelerate problem-solving, and continuously improve how we design and operate our data platforms. At Ridgeline, how we work matters as much as what we build. Ridgeliners act like owners, choose growth over comfort, and communicate with transparency. We assume positive intent, bias toward action, and bring solutions—not just problems. We celebrate wins, learn from setbacks, and thrive in a resilient, collaborative, high-performing culture. If this excites you, we’d love to meet you! You must be work authorized in the United States without the need for employer sponsorship. The impact you will have: Design and develop cloud-native data storage solutions that deliver scalable, reliable, and performant persistence across a multi-tenant SaaS platform Optimize data access patterns and collaborate with application teams to improve end-to-end performance at the application layer Drive RPO and RTO improvements by establishing high-availability architectures, failover strategies, and disaster recovery plans Support high-throughput, low-latency workloads through effective data partitioning, caching, and indexing strategies Improve observability by investing in database monitoring, automation, and performance telemetry Balance performance and efficiency by identifying and implementing cost optimizations across database infrastructure Collaborate transparently with cross-functional teams to solve complex data challenges and share best practices Mentor engineers, foster technical growth, and contribute to a resilient, inclusive culture of engineering excellence Take ownership of critical systems, acting with accountability and a long-term mindset aligned with Ridgeline’s values What we look for: 5+ years of experience in software or infrastructure engineering, with deep expertise in data persistence, distributed systems, or database engineering Proven experience building and operating distributed, multi-writer OLTP SQL systems (e.g., SingleStore, CockroachDB) and single-writer systems (e.g., Postgres), with a strong understanding of replication, sharding, and consistency tradeoffs Hands-on experience with OLAP or analytical data stores such as ClickHouse and/or Apache Iceberg on S3 Strong background in high availability and disaster recovery strategies, including cross-region replication, backups and point-in-time recovery, and clearly defined RPO/RTO targets Solid experience with AWS services such as Aurora RDS, S3, ECS, Lambda, and related infrastructure Proficiency in at least one programming language such as Kotlin, Java, or TypeScript Experience using Datadog or similar tooling for database and storage observability Proficiency with AI-assisted development tools such as Cursor, Claude, or GitHub Copilot S ... (truncated, view full listing at source)