Senior Data Engineer - Predict

Summary

Join Sword Health, a Forbes Best Startup Employer, and become a Senior Data Engineer on the Predict team. You will lead data initiatives, collaborating with the Predict team and the wider data engineering organization. The Predict platform forecasts healthcare trends and intervenes to reduce healthcare waste and improve lives. You will design, build, and maintain data pipelines, create data products for clients, and lead data architecture discussions. This role requires experience in data engineering, cloud infrastructure, big data technologies, and supporting AI/ML models. Sword Health offers competitive compensation, benefits, and a remote-first work environment.

Requirements

• Experience in data engineering, with a deep understanding of data pipelines, cloud infrastructure, and big data technologies
• Expertise in supporting AI/ML models—familiarity with LLMs and their integration into healthcare applications is a huge plus!
• A passion for creating data-driven solutions that enhance the healthcare experience and deliver real-world impact
• A collaborative mindset, able to work across interdisciplinary teams including AIresearchers, data scientists, and healthcare professionals
• Experience with cloud platforms (AWS, GCP, Azure) and scalable data frameworks (Spark, Kafka, etc.)
• Experience in designing and implementing scalable, efficient data pipelines, with a focus on SQL and modern data modeling techniques
• Experience in developing data engineering solutions using Python, and Pyspark, with particular experience in applying tools to AI and ML tasks

Responsibilities

• Will be helping Predict (one of Sword’s most important solutions) design, build, and maintain ETL/ELT data pipelines to efficiently ingest and process data from multiple sources
• Help us understand and create data products to be used by our external clients
• Lead thought around data architecture, data ingestion to make sure we are building robust processes and systems
• Collaborate with engineering/product/analyst teams

Preferred Qualifications

• Proven track record of creating data platforms for production-ready ML models, including model deployment, monitoring, and retraining
• Understanding of data ingestion systems and tradeoffs to make when ingesting Petabytes of data vs MBs of data

Benefits

• $138,830 - $218,161 a year
• Base: $119,000 - $187,000
• Variable: $9,450 - $14,850
• Net equity value per year: $10,380 - 16,311
• Comprehensive health, dental and vision insurance*
• Life and AD&D Insurance*
• Financial advisory services*
• Supplemental Insurance Benefits (Accident, Hospital and Critical Illness)*
• Health Savings Account*
• Equity shares*
• Discretionary PTO plan*
• Parental leave*
• 401(k)
• Flexible working hours
• Remote-first company
• Paid company holidays
• Free digital therapist for you and your family