Senior data platform engineer

Company details

Description of the offer

Ellipsis Health is creating cutting-edge AI/ML products that solve healthcare staffing issues and administrative burdens using conversation-based software and our patented voice biomarker technology. We are headquartered in Silicon Valley and are funded and supported by some of the most preeminent venture capital teams such as Khosla Ventures, Generator Ventures, Luminous Ventures, SpringTide Ventures, CityLight Capital, and SJF Ventures.

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

• Lead the design, development, and operation of a scalable and secure data platform to support analytics, ML Ops, and business intelligence
• Collaborate closely with Data Science, Machine Learning, and DevOps teams to implement end-to-end ML Ops pipelines
• Architect and manage data warehousing solutions using Databricks, Snowflake, and Spark
• Develop and maintain ETL/data pipelines that handle structured and unstructured data across diverse sources
• Optimize data storage, access, and processing for cost-efficiency and performance in AWS and Google Cloud environments
• Build and maintain dashboards and analytics solutions using tools such as Metabase, Sigma, and other BI platforms
• Ensure compliance with data governance, security, and privacy best practices, including HIPAA, SOC-2, and other regulatory requirements
• Evaluate and integrate third-party anonymization and security solutions to protect sensitive data
• Provide strategic guidance on the evolution of the data platform to meet the company’s growth and technical needs
• Design and implement scalable infrastructure for Large Language Model (LLM) operations, including training, fine-tuning, and inference workflows
• Collaborate with AI/ML teams to build and optimize LLM serving platforms for real-time and batch processing
• Develop monitoring and observability solutions for LLMs, ensuring model performance, cost-efficiency, and compliance with ethical AI guidelines
• Implement and optimize vector databases, retrieval-augmented generation (RAG) pipelines, and distributed model-serving architectures
• Evaluate and integrate state-of-the-art LLM technologies into existing data platforms to enhance analytics and decision-making

Qualifications

• Bachelor’s or Master’s Degree in Computer Science or equivalent experience
• 5+ years of industry experience in designing and building large-scale data platforms
• Strong expertise in SQL, Data Modeling, and Data Warehousing (Snowflake, Databricks, Redshift, BigQuery, etc.)
• Deep experience with Apache Spark and distributed data processing frameworks
• Proficiency in Python and shell scripting for data engineering and automation
• Hands-on experience with modern ETL/Orchestration frameworks such as Airflow, dbt, and others
• Experience working with ML Ops platforms and supporting Data Science teams
• Knowledge of business intelligence tools such as Metabase, Sigma, Tableau, and Looker
• Strong familiarity with cloud-based infrastructure and managed data services in AWS and Google Cloud
• Understanding of data governance, privacy, and regulatory frameworks (HIPAA, SOC-2, HITRUST)
• Experience in deploying and managing Large Language Models (LLMs) in production, including model versioning, inference scaling, and fine-tuning workflows
• Familiarity with vector databases (e.g., FAISS, Weaviate, Pinecone) and retrieval-augmented generation (RAG) architectures

Nice to Have

• Experience with ML Ops tools such as MLflow, Streamlit, and vector databases
• Familiarity with healthcare data standards (FHIR, HL7)
• Experience in real-time data processing and event-driven architectures
• Expertise in implementing data access controls and anonymization techniques

Benefits

• Competitive salary based on region and experience
• Meaningful stock options
• Unlimited PTO policy
• Health insurance (medical, dental, vision)
• 401(k) with match

Location of employment

How to apply?