Data Platform Engineer
US$150,000 – US$170,000 / yr base salary
Posted 5 Jun 2026
Advertised as “Senior Data Platform Engineer”
BranchFactor Summary
The original posting with the fluff stripped out
- Management level
- Individual contributor
- Employment
- Hybrid
- Contract
- Full-time
| Base salary | US$150,000 – US$170,000 / yr |
|---|
Field of studyComputer Science
Study levelBachelor's or higher
Ellipsis Health is creating cutting-edge AI/ML products that solve healthcare staffing challenges and administrative burdens using conversational AI and our patented voice biomarker technology - helping deliver better healthcare for everyone.
We are currently looking for an experienced Senior Data Platform Engineer, with significant experience in building, scaling, and optimizing modern data platforms across public cloud environments.
We are located in the San Francisco Bay Area, but we are open to remote candidates for this role anywhere in the US.
Responsibilities:
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Lead the design, development, and operation of a scalable and secure data platform to support analytics, ML Ops, and business intelligence
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Collaborate closely with Data Science, Machine Learning, Application and DevOps teams to implement end-to-end ML Ops pipelines
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Architect and manage data warehousing solutions using Databricks, Dbt, and Spark
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Develop and maintain ETL/data pipelines that handle structured and unstructured data across diverse sources
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Optimize data storage, access, and processing for cost-efficiency and performance in GCP and AWS Cloud environments
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Build and maintain dashboards and analytics solutions using tools such as Sigma, Metabase, and other BI platforms
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Ensure compliance with data governance, security, and privacy best practices, including HIPAA, SOC-2, and other regulatory requirements
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Evaluate and integrate third-party anonymization and security solutions to protect sensitive data
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Provide strategic guidance on the evolution of the data platform to meet the company's growth and technical needs
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Design and implement scalable infrastructure for Large Language Model (LLM) operations, including training, fine-tuning, and inference workflows
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Collaborate with AI/ML teams to build and optimize LLM serving platforms for real-time and batch processing
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Develop monitoring and observability solutions for LLMs, ensuring model performance, cost-efficiency, and compliance with ethical AI guidelines
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Evaluate and integrate state-of-the-art LLM technologies into existing data platforms to enhance analytics and decision-making
Qualifications:
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Bachelor's or Master's Degree in Computer Science or equivalent experience