Senior Platform Engineer, Data Persistence

Ridgeline•New York, NY

1d•$146,000 - $172,000•Hybrid

About The Position

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.

Requirements

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
Strong problem-solving skills, clear communication, and a genuine interest in learning and continuous improvement

Nice To Haves

Experience designing and operating high-throughput JVM services and data-access libraries, with deep knowledge of threading, connection pooling, and saturation behavior (e.g., HikariCP)
Background in event-driven architectures using Kafka or Pub/Sub, including familiarity with Debezium, Kafka Connect, schema registries, or CDC workflows
Experience in fintech, investment management, or other highly regulated data environments

Responsibilities

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