Senior Data Engineer at Medisolv in Clarksville

Who We Are

Healthcare quality is complex. Medisolv helps make it manageable — and actionable.

We partner with hospitals, health systems, ACOs, and payers to bring clarity to quality data, connecting clinical and claims information into a single, reliable view. More than 1,800 organizations and 130M+ patient records rely on Medisolv to measure, report, and improve performance across 500+ measures tied to CMS, The Joint Commission, and other programs.

With support from Bessemer Venture Partners Forge, we're continuing to grow our platform and expand our impact — investing in advanced analytics, AI, and new capabilities that help healthcare organizations stay ahead of change and improve outcomes with confidence.

Reporting to Director of AI & Data Engineering, we are looking for an experienced Senior Data Engineer to join our team.

About the Role

The Senior Data Engineer will provide hands-on technical leadership for Medisolv's healthcare data platform and customer implementations. You will design, build, and operate reliable data products that transform payer and quality data into trusted measure calculations, forecasts, and decision-ready insights.

This is a senior individual-contributor role with broad ownership across Snowflake, dbt, orchestration, cloud infrastructure, CI/CD, data quality, and production operations. You will partner closely with product, domain experts, application engineers, security, and client-facing teams while helping the engineering team establish scalable patterns and sound technical decisions.

What You'll Do

• Own the design and evolution of scalable Snowflake and dbt data models supporting healthcare quality measurement, forecasting, reporting, and customer-specific workflows.

• Lead complex ingestion and connector implementations for claims, enrollment, eligibility, pharmacy, survey, plan, and reference data delivered through SFTP, object storage, data shares, and APIs.

• Set engineering patterns for orchestration, incremental processing, dependency management, reruns, reconciliation, and production support across Airflow and related workflows.

• Drive cloud modernization work across AWS and Azure, including Terraform-based infrastructure, secure connectivity, secrets management, environment promotion, and operational readiness.

• Strengthen CI/CD and release practices using GitHub Actions and related tooling, with automated tests, security checks, observability, and controlled production deployment.

• Translate healthcare quality requirements into maintainable technical designs, partnering with domain experts on CMS Star Ratings, HEDIS, CAHPS, HOS, PQA, measure calculations, and scenario modeling.

• Investigate complex data and platform issues, lead root-cause analysis, and implement durable improvements to reliability, performance, cost, and data trust.

• Provide technical mentorship through architecture reviews, pull-request feedback, documentation, and reusable patterns without direct people-management responsibility.

• Collaborate with product, client delivery, security, and engineering leaders to scope work, surface dependencies, communicate tradeoffs, and deliver against customer commitments.

What You'll Accomplish — Your Performance Objectives

In your first 30 days, you will:

• Build working knowledge of the Lilac platform, healthcare-quality domain, Snowflake/dbt model layers, orchestration, cloud environments, release processes, and active customer commitments.

• Partner with engineering and domain leads to map critical data flows from ingestion through measure calculation, forecasting, reporting, and application consumption.

• Review current architecture, operational risks, and the AWS-to-Azure migration plan; complete an initial production-support shadowing cycle.

In your first 60 days, you will:

• Assume technical ownership of a meaningful data-platform or customer-integration workstream, including design, implementation plan, tests, observability, and rollout criteria.

• Deliver or materially advance a production-ready Snowflake/dbt, ingestion, or cloud-infrastructure enhancement with measurable quality or reliability outcomes.

• Establish clear design and review practices for the workstream and mentor teammates through code, model, and infrastructure reviews.

In your first 90 days, you will:

• Independently lead a cross-functional delivery from requirements through production validation, including dependency management, data reconciliation, release coordination, and post-release monitoring.

• Recommend and begin implementing prioritized improvements to scalability, test coverage, operational resilience, security, or cloud portability.

• Be a trusted technical owner for a core platform area and a reliable partner for healthcare-domain, product, and customer-delivery stakeholders.

Who We're Looking For — The Competencies That Matter

Required

• Substantial professional experience building and operating production data platforms, with senior-level ownership of architecture, delivery, and operational outcomes.

• Advanced SQL and data-modeling expertise, including hands-on production experience with Snowflake and dbt or closely comparable modern cloud-warehouse tooling.

• Experience designing robust batch data pipelines and ingestion frameworks, including schema mapping, incremental processing, testing, reconciliation, and failure recovery.

• Strong software engineering skills in Python or another production language, with disciplined version control, code review, automated testing, and documentation practices.

• Hands-on experience with infrastructure as code and CI/CD, including Terraform and GitHub Actions or comparable tools.

• Experience operating across AWS and/or Azure, with practical knowledge of networking, identity, secrets, object storage, monitoring, and secure environment design.

• Demonstrated ability to lead complex technical work across engineering, product, domain, security, and client-facing stakeholders.

• Commitment to secure handling of regulated healthcare data, least-privilege access, auditability, and production reliability.

Strongly Preferred

• Healthcare payer data experience, especially Medicare Advantage, CMS Star Ratings, HEDIS, CAHPS, HOS, PQA, claims, enrollment, eligibility, pharmacy, or quality-measure calculations.

• Experience with Apache Airflow or comparable orchestration and with targeted reruns, backfills, data-quality monitoring, and production incident response.

• Experience migrating data platforms or containerized workloads from AWS to Azure, including Azure App Service, Key Vault, Blob Storage, Private Link, or Azure DevOps Pipelines.

• Experience with forecasting, What-If/scenario modeling, financial or reward calculations, semantic models, or customer-specific analytics products.

• Experience with Go/Golang, OIDC/SAML/RBAC, Cognito or enterprise identity integrations, Sigma, or Snowflake-native analytics capabilities.

What You Bring — Professional Qualifications

• Bachelor's degree in computer science, engineering, information systems, data science, or a related discipline, or equivalent practical experience.

• Professional certifications in Snowflake, dbt, AWS, Azure, or Terraform are helpful but not required.

• Clear written and verbal communication, sound judgment under operational pressure, and the ability to make complex technical tradeoffs understandable.

How to Be a Medisolver — Our Values

• Customer Success Obsession

• All-Star Team Collaboration

• Continuous Improvement through Curiosity & Data-Driven Learning

• Courage with Kindness

• Execution Focus — We Do Business, Not Just Talk Business

Medisolv is committed to creating a diverse and inclusive workplace. We believe that diversity drives innovation, and we are dedicated to fostering an environment where all employees feel valued and respected.

All candidates must successfully pass a pre-employment background check and be legally authorized to work in the United States. Sponsorship is not available. This is a U.S.-based/onshore role supporting work with regulated and PHI-sensitive healthcare data.