Data Engineer (Healthcare Data Pipelines)

spike technologies • Lithuania
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AI Summary

Join Spike Technologies as a Data Engineer to design, implement, and maintain robust batch and streaming ETL/ELT pipelines for healthcare data. Analyze Voice AI agent performance and architect clean, production-grade data models in our cloud data warehouse. Ensure data observability and compliance with HIPAA protocols.

Key Highlights
Design and implement healthcare data pipelines
Analyze Voice AI agent performance
Ensure data observability and compliance
Key Responsibilities
Build and scale healthcare data pipelines
Develop product and LLM analytics
Own the analytics layer and modeling
Ensure data observability and compliance
Technical Skills Required
Data Engineering Data Warehousing ETL/ELT pipelines Cloud data warehouse Data modeling Data analytics
Benefits & Perks
Competitive salary and stock options package
Hybrid working model
USA work visa sponsorship and relocation to Silicon Valley HQ

Job Description


Spike Technologies Inc. is a VC-backed hyper growth B2B Agentic AI and health data startup founded in 2022, split between San Francisco, California, and Vilnius, Lithuania. Spike provides a multimodal Voice AI-powered platform designed to eliminate administrative burden in the healthcare industry. The company serves a diverse client base across healthcare, government, digital health and health insurance sector.


We are looking for Data Engineer to join Spike AI Engineering team.


Core Responsibilities:


  • Build & Scale Healthcare Data Pipelines: design, implement, and maintain robust batch and streaming ETL/ELT pipelines to ingest, normalize, and model complex healthcare datasets
  • Develop Product & LLM Analytics: build the data frameworks necessary to analyze Voice AI agent performance, such as tracking conversion/success rates of autonomous phone calls, pinpointing where LLMs misinterpret payer rules, and measuring automated claim appeal success.
  • Own the Analytics Layer & Modeling: architect clean, production-grade data models in our cloud data warehouse using modern modeling practices. Act as the bridge between raw engineering logs and clinic-ready analytics.
  • Ensure Data Observability & Compliance: implement rigorous data quality monitoring, schema validation, and observability frameworks. Ensure all analytical data stores strictly adhere to HIPAA compliance, data minimisation, and PHI segregation protocols.


Qualifications


  • Experience: at least 4 years of experience in Data Engineering, Analytics Engineering, or a highly technical Data Analyst role.
  • Data Warehousing: strong experience designing scalable dimensional data models within modern cloud data warehouses
  • Analytical & Business Acumen: ability to translate abstract technical system outputs into concrete product KPIs.
  • Ownership & Agility: high degree of initiative, comfortable wearing both "engineer" and "analyst" hats in a fast-paced, rapidly shifting startup environment.


What we offer:


  • Competitive salary and stock options package with a significant upside.
  • Hybrid working model (offices in Vilnius, Lithuania and Palo Alto, CA)
  • USA work visa sponsorship and relocation to Silicon Valley HQ where applicable
  • Dynamic growth: dive into AI and Data tech, seizing high-growth opportunities with cutting-edge projects.
  • Talented peers: collaborate with a smart, ambitious team comprising data scientists, PhDs, Cambridge alumni, and tech industry pros (formerly from Bloomberg, Amazon, and Google).
  • Solid backing: enjoy stability and ample resources for success, supported by reputable venture capitalists.


At Spike Technologies, diversity is celebrated, and inclusion is our priority. We welcome applicants from all backgrounds to join our innovative team and contribute to our inclusive culture.


Sounds like you? Let's talk.


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