Senior Data Platform Engineer

Ellipsis Health; United States; Remote; USD 150,000 - 170,000; Full time

Benefits offered by this job

401(k) matching

Health, vision, dental insurance

Flexible paid time off

Job summary

Ellipsis Health is seeking an experienced Senior Data Platform Engineer to design, build, and scale a modern data platform across AWS and GCP, supporting analytics, ML Ops, and BI. You will partner with Data Science, ML, Applications and DevOps teams to deliver end-to-end pipelines and secure data infrastructure.

You will architect data warehousing with Databricks, dbt, and Spark, develop ETL pipelines, and optimize costs and performance while ensuring governance and privacy compliance.

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 (Databricks, Snowflake, Redshift, BigQuery, etc).
• Proficiency in writing Advanced SQLs and performance tuning.
• Strong proficiency in Python for building, optimizing, automating and maintaining data pipelines and services.
• Deep experience with Apache Spark and distributed data processing frameworks.
• Hands-on experience with modern ETL/Orchestration frameworks such as Airflow, dbt, and others.
• Knowledge of BI tools such as Sigma, Metabase, Tableau, and Looker.
• Strong familiarity with cloud-based infrastructure and managed data services in GCP and AWS.
• Experience with CI/CD pipelines to automate testing, deployment and release of data engineering and analytics workflows.
• Experience with tools like Kubernetes, Terraform, Pubsub, Debezium.
• Exposure building data quality frameworks and automation.
• Understanding of data governance, privacy, and regulatory frameworks (HIPAA, SOC-2, HITRUST)

Responsibilities

• Lead the design, development, and operation of a scalable data platform for analytics, ML Ops, and BI.
• Collaborate with Data Science, ML, Applications and DevOps teams to implement ML Ops pipelines.
• Architect and manage data warehousing solutions using Databricks, dbt, and Spark.
• Develop and maintain ETL/data pipelines across diverse sources.
• Optimize data storage and processing for cost-efficiency and performance in GCP/AWS.
• Build dashboards and analytics using Sigma, Metabase, and other BI tools.
• Ensure compliance with data governance, security, and privacy requirements (HIPAA, SOC-2, etc).
• Design and implement scalable infra for LLM operations, including training and inference workflows.
• Collaborate with AI/ML teams to optimize LLM serving platforms for real-time and batch processing.
• Develop monitoring/observability for LLMs, ensuring performance and cost-efficiency.
• Evaluate and integrate state-of-the-art LLM tech to enhance analytics and decision-making.

Skills

SQL

Python

Apache Spark

Data Modeling

Data Warehousing

Education

Bachelor's or Master's in Computer Science or equivalent

Tools

Databricks

dbt

Airflow

Kubernetes

Terraform

Job description

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:

• 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, Application and DevOps teams to implement end-to-end ML Ops pipelines

• Architect and manage data warehousing solutions using Databricks, Dbt, 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 GCP and AWS Cloud environments

• Build and maintain dashboards and analytics solutions using tools such as Sigma, Metabase, 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

• 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 (Databricks, Snowflake, Redshift, BigQuery, etc.)

• Proficiency in writing Advanced SQLs and performance tuning

• Strong proficiency in Python for building, optimizing, automating and maintaining data pipelines and services

• Deep experience with Apache Spark and distributed data processing frameworks

• Hands-on experience with modern ETL/Orchestration frameworks such as Airflow, dbt, and others

• Knowledge of business intelligence tools such as Sigma, Metabase, Tableau, and Looker

• Strong familiarity with cloud-based infrastructure and managed data services in GCP and AWS Cloud

• Experience with CI/CD pipelines to automate testing, deployment and release of data engineering and analytics workflows using GitLab, GitHub etc

• Experience with tools like Kubernetes, Terraform, Pubsub, Debezium

• Exposure building data quality frameworks and automation

• Understanding of data governance, privacy, and regulatory frameworks (HIPAA, SOC-2, HITRUST)

Nice to Have:

• Experience working with ML Ops platforms and supporting Data Science teams

• 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

Salary and Benefits:

We offer competitive salary and benefits, including 401(k) matching, health, vision, and dental insurance, and very flexible paid time off.

The typical salary range for this role is $150,000 to $170,000 USD, depending on skills, qualifications, and relevant experience.

Background Checks:

As a health technology company, we reserve the right to run background checks on candidates to whom we extend offers, in compliance with applicable laws. We evaluate candidates holistically and comply with all "ban the box" regulations.

Assistance:

If you have a disability or require accommodations during the application or recruitment process, please contact [e-mail].