Vatica Health

Risk adjustment and quality-of-care solutions

Senior Data Engineer

Data EngineeringPosted on Nov 10

Full-timeRemote in USARemote

About the Job

Requirements

The candidate must have 8–10 years of professional experience in data engineering or a related field.
The candidate must have strong Python and advanced SQL skills, including experience delivering production data pipelines at scale.
The candidate must have hands-on experience with at least one workflow orchestration platform and big data processing frameworks.
The candidate must have experience developing and deploying production REST APIs, including integration, security, and automated testing.
The candidate must have experience with cloud platforms and data services.
The candidate must understand data warehousing, lakehouse architecture, and data modeling.
The candidate must have working knowledge of AI and machine learning workflows, large language model APIs, embeddings, and vector databases.
The candidate must have experience with Git, continuous integration and continuous delivery, Docker, and infrastructure-as-code tools such as Terraform.
The candidate must have strong problem-solving, communication, and stakeholder management skills.

Responsibilities

Design, build, and maintain batch and streaming pipelines for structured and unstructured data from databases, APIs, event streams, and files.
Develop extract-transform-load and extract-load-transform processes, and optimize performance, cost, scalability, and reliability.
Build and operate cloud solutions using AWS services such as EC2, ECS, Lambda, API Gateway, and SQS.
Develop and manage data workflows, including scheduling, dependencies, retries, alerts, and backfills.
Establish monitoring, logging, and observability to identify issues and support reliable production operations.
Design, develop, test, and maintain secure REST APIs and Python-based data services using frameworks such as FastAPI or Flask.
Implement API authentication, authorization, validation, versioning, error handling, rate limiting, and documentation.
Build data foundations for machine learning and generative AI, including feature pipelines, training and inference datasets, embeddings, and retrieval-based solutions.
Integrate AI tools and large language model APIs into workflows for document processing, enrichment, classification, and summarization.
Implement data quality checks, validation, lineage, and documentation, applying security, privacy, and compliance standards.
Lead architecture and code reviews, mentor engineers, and communicate technical recommendations to business and technical stakeholders.

Desired Qualifications

Experience building and operating solutions on AWS.
Experience delivering retrieval-augmented generation or agent-based solutions in production.
Knowledge of data governance, cataloging, and lineage tools.
Cloud or data platform certifications.
Healthcare industry experience.
A bachelor's or master's degree in Computer Science, Engineering, or a related field.

Senior Data Engineer

Vatica Health · United States (Remote) · Full-time · Posted 2026-11-10

Salary: USD 115,000–125,000

Workplace: remote

Department: Data Engineering

Description

Vatica Health and Cozeva bring together clinical expertise and technology to support risk adjustment, quality, and value-based care. Our teams help providers and health plans use clinical information to improve documentation and identify care gaps.

About the Role

As a Senior Data Engineer, you will design, build, and operate the data pipelines and APIs that support our data-driven and AI-enabled products. You will own how data moves from ingestion through consumption, ensuring it is reliable, secure, and available for the teams and products that depend on it.

You will partner with product, analytics, data science, and machine learning teams to translate business needs into scalable production solutions. This hands-on role also includes leading technical reviews, establishing engineering standards, and mentoring other engineers.

Responsibilities

Design, build, and maintain batch and streaming pipelines for structured and unstructured data from databases, APIs, event streams, and files.
Develop ETL/ELT processes and optimize performance, cost, scalability, and reliability.
Build and operate cloud solutions using AWS services such as EC2, ECS, Lambda, API Gateway, and SQS.
Develop and manage data workflows, including scheduling, dependencies, retries, alerts, and backfills.
Establish monitoring, logging, and observability to identify issues and support reliable production operations.
Design, develop, test, and maintain secure REST APIs and Python-based data services using frameworks such as FastAPI or Flask.
Implement API authentication, authorization, validation, versioning, error handling, rate limiting, and documentation.
Build data foundations for machine learning and generative AI, including feature pipelines, training and inference datasets, embeddings, and retrieval-based solutions.
Integrate AI tools and large language model (LLM) APIs into workflows for document processing, enrichment, classification, and summarization.
Implement data quality checks, validation, lineage, and documentation, applying security, privacy, and compliance standards.
Lead architecture and code reviews, mentor engineers, and communicate technical recommendations to business and technical stakeholders.

Requirements

Required Qualifications

8–10 years of professional experience in data engineering or a related field.
Strong Python and advanced SQL skills, with experience delivering production data pipelines at scale.
Hands-on experience with at least one workflow orchestration platform and big data processing frameworks.
Experience developing and deploying production REST APIs, including integration, security, and automated testing.
Experience with cloud platforms and data services.
Understanding of data warehousing, lakehouse architecture, and data modeling.
Working knowledge of AI and machine learning workflows, LLM APIs, embeddings, and vector databases.
Experience with Git, CI/CD, Docker, and infrastructure as code tools such as Terraform.
Strong problem-solving, communication, and stakeholder management skills.

Preferred Qualifications

Experience building and operating solutions on AWS.
Experience delivering retrieval-augmented generation (RAG) or agent-based solutions in production.
Knowledge of data governance, cataloging, and lineage tools.
Cloud or data platform certifications.
Healthcare industry experience.
Bachelor’s or master’s degree in Computer Science, Engineering, or a related field.

Benefits

WORKING AT VATICA HEALTH ADVANTAGES

Prosperity

Competitive salary based on your experience and skills – we believe the top talent deserves the top dollar
Bonus Potential (based on role and is discretionary) – if you go above and beyond, you should be rewarded
401k plans– we want to empower you to prepare for your future
Room for growth and advancement- we love our employees and want to develop within

Good Health

Comprehensive Medical, Dental, and Vision insurance plans
Tax-free Dependent Care Account
Life insurance, short-term, and long-term disability

Happiness

Excellent PTO policy (everyone deserves a vacation now and then)
Great work-life balance environment- We believe family comes first!
Strong supportive teams- There is always a helping hand when you need it

Apply

Apply at Vatica Health

About the Company

Vatica Health

Risk adjustment and quality-of-care solutions

Vatica Health provides risk adjustment and quality-of-care solutions to healthcare providers, health plans, and patients. Its products help clinicians capture accurate health data at the point of care, using proprietary technology that speeds up coding so clinicians can spend more time delivering care. The platform emphasizes compliance to lower audit risk and supports the delivery of Annual Wellness Visits and preventive services. Revenue comes from partnerships with providers and health plans, with growth aided by strategic investment (notably from Great Hill Partners since 2019). The company differentiates itself through a clear focus on compliance and financial performance improvements enabled by its proprietary technology. Its goal is to transform the risk adjustment industry by improving patient outcomes and the financial health of its clients through efficient, compliant clinical encounters.

Company size: 201-500
Company stage: Early VC
Total funding: $1.2M
Headquarters: Georgia, United States
Founded: 2012

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