Senior Data Platform Engineer

🕒 April 29

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Sword Health

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2015

⚕️ Healthcare Insurance

🤖 Artificial Intelligence

🧘 Wellness

Healthcare Insurance • Artificial Intelligence • Wellness

Sword Health is a digital health company that combines artificial intelligence with clinical expertise to provide world-class care for muscle, joint, and pelvic health conditions. By offering digital physical therapy and AI-driven care, Sword helps individuals recover from physical ailments from the comfort of their own home, avoiding surgeries and reducing the need for medications. The company provides employers, health plans, and individuals with personalized treatment plans that are cost-effective and have proven outcomes in pain reduction and improved productivity. Sword Health is dedicated to expanding access to high-quality care and ensuring health equity across global communities.

📋 Description

• Design and evolve Sword’s streaming lakehouse — the foundation that every data consumer in the company depends on. • Build and operate distributed streaming pipelines that move data at low latency and high reliability. • Own the durable workflows that coordinate complex data movement across systems. • Shape the platform’s API surface — the interface producers and consumers use so they never need to touch infrastructure. • Drive evaluations and integrations with vendor data platforms, sitting inside the architectural trade-offs rather than just consuming the output. • Contribute to the self-service and agentic layer: interfaces designed to be consumed by humans, systems, and AI agents alike. • Partner with data engineers and analysts on contracts, governance, and lineage. • Build and maintain AI-ready data infrastructure that powers ML and AI-driven products across Sword. • Leverage AI coding assistants and LLMs to accelerate development, automate documentation, and raise code quality. • Work in a regulated environment where audit, compliance, and governance are part of every design.

🎯 Requirements

• Proven experience designing and operating data platforms at scale — warehouse, data lake, or lakehouse architectures in production. • Hands-on experience with a modern lakehouse table format — Iceberg strongly preferred; Delta Lake or Hudi also welcome. You understand how the format works under the hood: metadata layout, snapshots, manifests, compaction, copy-on-write vs. merge-on-read. • Clear mental model of catalogs (REST, Polaris, Glue, Unity, Hive) — their trade-offs, and how compute stays detached from storage. • Exposure to at least one vendor lakehouse or query platform — Snowflake, Starburst, or Databricks — at the level where you can reason about its architecture, not just use its UI. • Strong experience with a distributed processing engine — Flink strongly preferred; Spark also fine. You can reason about its internals, fine-tune a running job, and debug a pipeline that’s silently degrading. • Familiarity with durable execution — Temporal, Restate, or similar — or at minimum a solid mental model of what durable execution means and why it matters for data workflows. • Production experience building and operating APIs (REST or gRPC) at scale — good instincts about contracts, versioning, retries, rate limiting, and observability. • Solid understanding of Kafka and event-driven architectures (producers/consumers, partitioning, delivery semantics). • Comfortable in regulated environments (healthcare, fintech, gov) where audit, compliance, and data governance are part of every design. • Platform mindset: you design for self-service, API-first, and with systems and agents — not only humans — as legitimate consumers.

🏖️ Benefits

• Health, dental and vision insurance • Meal allowance • Equity shares • Remote work allowance • Flexible working hours • Work from home • Discretionary vacation • Snacks and beverages