Senior Data Engineer - Data Platform

Sword Health is shifting healthcare from human-first to AI-first through its AI Care platform, making world-class healthcare available anytime, anywhere, while significantly reducing costs for payers, self-insured employers, national health systems, and other healthcare organizations. Sword began by reinventing pain care with AI at its core, and has since expanded into women’s health, movement health, and more recently mental health. Since 2020, more than 700,000 members across three continents have completed 10 million AI sessions, helping Sword's 1,000+ enterprise clients avoid over $1 billion in unnecessary healthcare costs. Backed by 42 clinical studies and over 44 patents, Sword Health has raised more than $500 million from leading investors, including Khosla Ventures, General Catalyst, Transformation Capital, and Founders Fund. Learn more at www.swordhealth.com .

Architect a scalable lakehouse by migrating workloads to Apache Iceberg. You’ll develop a Jobs API, build Spark/Flink pipelines, and establish data contracts. Requires proficiency in Python and Kafka with a platform-first, collaborative mindset.

At Sword Health , data is at the core of our mission to build a pain-free world. Our Data Team plays a central role in enabling a truly data-driven organization, ensuring that every decision is guided by reliable, actionable insights that directly impact millions of lives worldwide.

What you’ll be doing:

• Spearhead the migration of existing workloads to the Iceberg format, establishing and maturing the foundational lakehouse architecture.
• Architect and construct robust batch and streaming data pipelines utilizing Spark and Flink technologies.
• Collaborate closely with the Backend Engineering team on API integrations and the establishment of formal data contracts.
• Contribute to the development of a unified lineage and governance framework utilizing DataHub.
• Provide comprehensive support to the Core Team in the successful adoption of new data platform capabilities.

What you need to have:

• Demonstrated proficiency with Python and PySpark.
• Hands-on experience with data lake formats (e.g., Iceberg, Delta Lake, or Hudi).
• Solid understanding of Kafka and event-driven architectures.
• Experience in building and orchestrating data pipelines at scale.
• Strong SQL proficiency and comprehensive data modeling knowledge.
• Familiarity with workflow orchestration tools (e.g., Airflow, Dagster, or similar).
• Platform-oriented mindset: developing solutions for broad organizational use, not solely individual purposes.
• Ownership mentality: committed to seeing problems through to resolution.
• Clear communication skills: ability to articulate complex technical concepts to non-technical stakeholders.
• Highly collaborative: excels in working alongside backend engineers, data engineers